Socialization, Moral Judgment, and Action: A Sociological Dual-Process Model of Outcomes 3030882772, 9783030882778

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Socialization, Moral Judgment, and Action A Sociological Dual-Process Model of Outcomes lu i s a n t on io v i l a-h e n n i nge r

Socialization, Moral Judgment, and Action

Luis Antonio Vila-Henninger

Socialization, Moral Judgment, and Action A Sociological Dual-Process Model of Outcomes

Luis Antonio Vila-Henninger Department of Political Science Aarhus University Aarhus, Denmark ISPOLE UCLouvain Louvain-la-Neuve, Belgium

ISBN 978-3-030-88277-8    ISBN 978-3-030-88278-5 (eBook) https://doi.org/10.1007/978-3-030-88278-5 © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

For Chax and Harvey

Acknowledgments

I would like to thank Terrence Hill for his extensive feedback throughout the entirety of my analysis for Chap. 6 and Kenneth Forster for his oversight, guidance, and feedback throughout the entirety of the experiment I used in Chap. 7. I would also like to thank Stephen Vaisey for sharing information relevant to my approximate replication of his 2009 analysis and variables, as well as John P. Hoffmann for sharing information relevant to my replication of several variables from his 2014 analysis. I would like to thank Maitham Naeemi from the Allen Institute for Brain Science for providing me with feedback on my understanding of neuroscience and preliminary feedback on the framework for this book, as well as Albert Bergesen for mentorship in culture and cognition early in my graduate career, and the University of Arizona’s Cognitive Science program for my formal graduate training in cognitive science. Finally, I thank Rosario De La Luz Rizzo Lara for her support and feedback. The National Study of Youth and Religion, http://youthandreligion. nd.edu/ whose data were used by permission here, was generously funded by Lilly Endowment Inc., under the direction of Christian Smith, of the Department of Sociology at the University of Notre Dame, and Lisa Pearce, of the Department of Sociology at the University of North Carolina at Chapel Hill.

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Contents

1 Introduction  1 2 Conceptual Foundations for Theory-Building 17 3 Background: Models of Action and Socialization 29 4 The Dichotomy and the Data 53 5 Theory: A Sociological Dual-Process Model of Outcomes 93 6 Analysis Using Forced-Choice Self-Report Survey Data (National Study of Youth and Religion Waves 1 and 4)115 7 Analysis of Schemas Using an Experiment153 8 Conclusion169 Appendices175 Index191

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List of Figures

Fig. 5.1 Fig. 5.2 Fig. 5.3

Model of Type I outcome cognition in the neuroscience dual-process model of outcomes Model of Type II outcome cognition in the neuroscience dual-process model of outcomes Model of integrative outcome cognition in the neuroscience dual-­process model of outcomes

97 99 100

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List of Tables

Table 6.1

Table 6.2 Table 7.1 Table 7.2 Table 7.3 Table B.1 Table B.2 Table B.3

Logistic Regression: Odds Ratios for Wave 4 Reports of Respondent Incarceration (or having spent time in some type of correctional facility) At Least Once versus Not Incarcerated (or having spent time in some type of correctional facility) At All 138 Negative Binomial Regression: Number of Times Incarcerated (or having spent time in some type of correctional facility) Reported in Wave 4 Incident Rate Ratios 142 Mean reaction times (ms) for primed versus unprimed moral decisions163 Mean reaction times (ms) for primed versus unprimed moral decisions within subsets of the data according to moral decision 164 Effects on moral decision-making (agree/disagree) with full data set 164 Summary statistics with Wave 4 Panel Weight 176 Summary statistics with Wave 2 NSYR Survey Weight 178 Summary statistics with No Weight 179

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CHAPTER 1

Introduction

The question of causality is a central theme in the sociology of culture and is the central theme of this book. How does culture affect action? This has long been framed in terms of a means versus ends debate—in other words, do cultural ends (such as goals) or cultural means/resources (such as cultural repertoires)  play a primary causal role in human behavior? This debate has been addressed by scholars’ development of models of how culture affects individuals’ actions. However, socialization plays a key but relatively neglected causal role in cultural processes. To proceed, we must therefore understand both sides of the coin of causality in culture. My book contributes in four main ways: (1) It provides a critical overview of the literature that explains the limitations of the sociological dual-­ process model and subsequent scholarship (Chap. 4). (2) It provides a dual-process model of moral judgment that formally explains Type I processes, Type II processes, and the interaction between Type I and Type II processes (Chap. 5). (3) It expands the dual-process model to include a temporal dimension—and thus I create a “dual-process model of outcomes” (Chap. 5). (4) It develops empirical indicators of my model that confirm my theorization and contribute to literature on measures of dual-­ process models (Chaps. 6 and 7). Thus, I seek to contribute by pursuing several of the issues raised by Cerulo, Leschziner, and Shepherd (2021) for how to advance the subfield of the Sociology of Culture and Cognition.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 L. A. Vila-Henninger, Socialization, Moral Judgment, and Action, https://doi.org/10.1007/978-3-030-88278-5_1

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Models of Action The traditional perspective, stemming from the work of Max Weber, was that mostly conscious cultural ends—or interests—primarily affected human behavior (Weber 1946 [1922–3]: 280; Parsons and Shils 1951). Subsequent work pioneered by Ann Swidler argues instead that cultural means—such as cultural capacities and resources—mainly shape action (Swidler 1986, 2001, 2008; DiMaggio 1997, 2002; Sewell 2005; Mizrachi et  al. 2007; Martin 2010; Guetzkow and Ben-Zvi 2017; Mencken and Froese 2017; Rosen 2017). This perspective is called “Culture in Action” and argues that social structures pattern practices and collective meanings. Actors then use these practices and collective meanings—which are seen as cultural resources—in social interactions that facilitate their acquisition of additional practices and collective meanings. These cultural resources, or “toolkits,” structure behavior by limiting or providing the potential courses of behavior available to an actor. However, work from an alternative perspective based in the Bourdieusian tradition—which many call Strong Practice Theory (Lizardo and Strand 2010)—still championed the Weberian tradition concerning the causal importance of cultural ends—but with the twist that subconscious ends primarily affected action (Bourdieu 1984, 1990; Lizardo 2004, 2007, 2009, 2019; Ignatow 2007, 2009, 2019; Vaisey 2008a, 2008b, 2009, 2013; Vaisey and Lizardo 2010; Lizardo and Strand 2010; Miles 2015; Vaisey and Frye 2019). Bourdieu’s (1984, 1990) habitus is the foundation for this perspective. In this tradition, scholars have advanced a “dual-process model” (Haidt 2001; Vaisey 2009; Vaisey and Lizardo 2010; Vaisey and Frye 2019) to explain how unconscious means can affect action in the case of moral judgment. This model suggested that through cultural interaction, individuals develop moral “schemas”—or unconscious neural networks of associations built through experience (Vaisey 2009: 1686)—which automatically generate moral intuitions that “drive” action-oriented judgments concerning deviant or prosocial behavior (ibid.: 1698). Reasoning, conversely, was generated by post hoc “deliberative” cognition (ibid.: 1681)—“when required by social demands” (ibid.: 1687)—to socially  justify moral  judgments and actions driven by these automatic moral intuitions. Thus, there are two cognitive processes in the sociological dual-process model. The first (Type I) is fast, automatic, and intuitive. The second (Type II) is slow and deliberative.

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More broadly, scholars in the sociology of culture largely agree that there are two general types of cognition that characterize moral judgment and behavior (for summaries, see Lizardo et al. 2016: 292; Lizardo 2017: 90–1; Miles et  al. 2019; for reviews, see DiMaggio 1997, 2002; Vaisey 2009; Patterson 2014; Brekhus 2015; Turner 2018; Cerulo et al. 2021). “Type I” cognition occurs automatically without the actor’s awareness (e.g., intuition) and usually draws upon nondeclarative memory. Conversely, “Type II” cognition is characterized by deliberation (e.g., reasoning) and usually draws upon declarative memory. Subsequent work demonstrates how and when Strong Practice Theory’s dualism, or the division between Type I and Type II cognitive processes, breaks down—for example, depending on context or when actors use mental processes beyond moral judgment (Abramson 2012; Leschziner and Green 2013; Leschziner 2015; Winchester 2016; Cerulo 2018, 2019; Leschziner 2019; Leschziner and Brett 2019; Williams 2020; Bursell and Olsson 2021; Pagis and Summers-Effler 2021; Rawlings and Childress 2021). Further work has also demonstrated that these two processes interact, as well as that reasoning can affect action in important ways (Vila-­ Henninger 2015, 2020; Lizardo et al. 2016; Miles et al. 2019). Furthermore, a key element of the original sociological dual-process model of moral judgment is that Type I (automatic) and Type II (deliberative) processes often conflict (Vaisey 2009; Vaisey and Lizardo 2010). Subsequent work has then argued (Lizardo 2017: 97) that Type I and Type II are dissociated rather than in conflict. In this book, I will build on my previous work on dual-process models in order to develop a model of how culture affects action (Vila-Henninger 2015, 2020). In particular, I mobilize work in neuroscience that demonstrates how Type I and Type II processes not only acquire different elements of culture, but also translate these elements into action (Cushman 2013; Crockett 2013; Greene 2017; Lockwood et al. 2020). To proceed then, we need to understand socialization and its connection to action.

Socialization Socialization is a key component of models of action in the sociology of culture. Both Culture in Action (e.g., Swidler 1986, 2001) and Strong Practice Theory’s Dual-Process Model (e.g., Vaisey 2009; Vaisey and Lizardo 2010) stress the importance of understanding socialization in their models. However, these models mainly theorize socialization, rather

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than develop measures of how socialization affects action. This book seeks to do both. There are two main models of socialization in the sociology of culture. Kiley and Vaisey (2020) call these two models the “Active Updating Model” and the “Settled Dispositions Model” (for an extended discussion, see Vaisey and Lizardo 2016; Kiley and Vaisey 2020; Brett and Miles 2021;  Broć ić and Miles 2021; Guhin et al. 2021; Lizardo 2021). Each perspective corresponds to one of the major traditions in the sociology of culture concerning the role of causality. “Active Updating” is part of Culture in Action (e.g., Swidler 2001) and “Settled Dispositions” is a foundational feature of Strong Practice Theory (e.g., Bourdieu 1990). “Active Updating” argues that people’s socialization changes with the environment. As the environment and social interaction change, so do people’s dispositions and behaviors. Socialization is then a dynamic process that occurs throughout the life course (Joas 1996; Swidler 2001; Gross 2009; Kiley and Vaisey 2020). “Settled Dispositions,” however, argues that actors are primarily socialized during childhood. From early formative experiences, people then develop the dispositions that they tend to rely upon for the rest of their lives. Bourdieu’s concept of “habitus” is a classic example of this perspective (Bourdieu 1990; for summaries, see Vaisey and Lizardo 2016; Kiley and Vaisey 2020). Subsequent work on dual-process models has then argued that both of these perspectives come into play (Vaisey and Lizardo 2010, 2016; Srivastava and Banaji 2011; Hoffmann 2014; Miles 2015) and more recent work in Strong Practice Theory has also argued that both of these perspectives are useful (Lizardo and Strand 2010; Kiley and Vaisey 2020). For example, Kiley and Vaisey (2020) think that both models make important contributions and help to explain socialization. From their perspective, what is needed is more research on the “circumstances” in which each model applies. Ensuing scholarship then demonstrates different social factors that are more likely to trigger Type I (automatic) versus Type II (deliberative) cognition (Brett and Miles 2021). Crucially, however, recent work in this area has been limited to analyzing the relationship between socialization and attitudes (Vaisey and Lizardo 2016; Kiley and Vaisey 2020; Brett and Miles 2021). In this sense, these contributions help us understand the link between socialization and attitudes but not between socialization and action. While work on dual-process models of action has sought to bridge these two perspectives (Vaisey and Lizardo 2010, 2016; Srivastava and

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Banaji 2011; Hoffmann 2014; Miles 2015), other dual-process models provide the scaffolding to understand both processes of socialization (Vila-Henninger 2015, 2020; Lizardo et  al. 2016; Lizardo 2017). Key here is the distinction between Type I and Type II processes of socialization. However, within this work, there is debate over whether Type I and Type II processes of socialization occur in a model in which these two processes are dissociated and thus largely independent (Lizardo 2017: 97) or whether they exist in a model where Type I and Type II processes are also potentially in conflict or work together (Vila-Henninger 2015, 2020). In this book, I build on my previous work and outline a dual-process model in which Type I and Type II processes are both at times independent but are also in conflict or work together—depending on the context. To do so, I build on work in neuroscience (Cushman 2013; Crockett 2013; Greene 2017; Lockwood et al. 2020). Finally, scholars have noted a  distinction between socialization occurring through interaction versus through instruction (Guhin et al. 2021; Lizardo 2021). It is important to note that when I refer to “socialization” in the context of the dual-process model that I develop, I am referring to social learning regardless of the social process (i.e. via both instruction and interaction) because my theory accounts for both of these modes of internalization.

Agenda for This Book As this brief literature review demonstrates, understanding how culture affects action requires a model of action as well as a model of socialization. By socialization, I am referring to internalization through both interaction and instruction (Guhin et  al. 2021; Lizardo 2021).  This book will then develop a dual-process model of action—which for reasons I will discuss, I refer to as a “Dual-Process Model of Outcomes”—that incorporates a model of socialization. I then develop measures of Type I and Type II processes, as well as their conflict and cooperation. The later part of this book then presents these measures by using self-report survey data and an experiment. I do so largely by addressing two key gaps in the sociological dual-­ process model. Neither this model nor subsequent work in the sociology of culture have addressed either how Type II cognition is predictive of outcomes or how deliberation between competing Type I and Type II cognition is predictive of outcomes (Vaisey 2009; Vaisey and Lizardo 2010; Lizardo and Strand 2010; Martin 2010; Martin and Desmond 2010; Vaisey and Lizardo 2010; Abramson 2012; Leschziner and Green 2013; Hoffmann 2014; Patterson 2014; Miles 2014, 2015; Lizardo et al. 2016;

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Winchester 2016; Lizardo 2017; Moore 2017; Stoltz and Lizardo 2018; Miles et al. 2019). These two gaps are largely based on Bourdieu’s habitus—which is a foundation of the sociological dual-process model (Vaisey 2009; Vaisey and Lizardo 2010). To proceed, then, we must briefly review Bourdieu’s habitus (for a summary, see Bourdieu 1990; Wacquant 2016) as it relates to these gaps. Habitus argues that socialization occurs through automatic cognition in the development of dispositions. In his formal work, Bourdieu equated habitus with dispositions—which he describes as being automatic and embodied, and what the contemporary literature would describe as a type of Type I cognition. In a workshop, Bourdieu responded to critiques of habitus by arguing that actors can consciously override dispositions (Bourdieu and Wacquant 1992: 136–7)—or in contemporary terms, that Type II cognition can override Type I cognition. Furthermore, in the same workshop, Bourdieu seemed to reject the idea that actors deliberate between competing Type I and Type II cognitive processes (Bourdieu and Wacquant 1992: 137). This latter point is important because neuroscience has established that such deliberation is central to understanding moral reasoning (for a summary, see Greene 2017)—despite the claims of contemporary theorists (Lizardo 2017: 97). Bourdieu’s responses reveal two key gaps in habitus—and subsequently the sociological dual-process model. The first concerns how habitus could incorporate Type II cognition. The second consists of habitus’ incorporation of deliberation between competing Type I and Type II cognitive processes. Returning to Bourdieu’s focus on the consequences of socialization, the literature in the sociology of culture on habitus and socialization has largely overlooked the link between socialization and outcomes—defined here as the consequences of behavior (Gaddis 2013; for summaries, see Lizardo et al. 2016; Miles et al. 2019). The goal of this book is to develop a model that can empirically link socialization to its consequences in a way that applies habitus as well as incorporates Type II cognition and deliberation between competing Type I and Type II cognitive processes. Thus, in this book, I use habitus as a theoretical resource for understanding socialization. Rather than take a side on the socialization debate (for reviews, see Vaisey and Lizardo 2016; Kiley and Vaisey 2020; Brett and Miles 2021),  or describing socialization in philosophical language (Lizardo 2021), I build on work that lays out the theoretical and empirical

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scaffolding for understanding on a cognitive level how either perspective (“Active Updating” versus “Settled Dispositions”) takes place (Vila-­ Henninger 2015, 2020; Lizardo et al. 2016; Lizardo 2017). Thus, this book complements perspectives that see the question of socialization as empirical (Kiley and Vaisey 2020). A key step, however, is that in this book I develop measures that allow us to measure empirically how socialization affects action. To begin to fill these gaps, I use scholarship from neuroscience to develop a sociological “Dual-Process Model of Outcomes” (DPMO). This provides an empirical framework for theorizing the link between socialization and behavioral outcomes by providing a model from neuroscience that develops a model of Type I cognition (Model-Free Reinforcement Learning, or MFRL) and Type II cognition (Model Based Learning, or MBL) as they are linked to outcomes. Furthermore, this literature in neuroscience contributes by specifying that Type II cognition is involved in “integrative processes” (Greene 2017) that help to deliberate between competing Type I and Type II inputs during an actor’s decision-­making process. For my primary empirical analysis, I develop operationalizations for each of the model’s three cognitive processes—Type I automatic inputs, Type II deliberative inputs, and Type II deliberation between Type I and Type II inputs. I then apply these operationalizations to longitudinal forced-choice self-report survey data set in order to find connections between each of the aforementioned cognitive processes involved in socialization and a key outcome. Scholarship in this area uses longitudinal data to show associations between religious or moral socialization and deviant behavior (Vaisey 2009; Vaisey and Lizardo 2010; Hoffmann 2014). Building on this research, I investigate empirical links between DPMO socialization and outcomes of deviant behavior. For this analysis, I chose respondent incarceration as the dependent variable. It is important to note that recent work (Miles et al. 2019) highlights the difficulties of using standard forced-choice self-report survey items to measure automatic cognition (Type I) in the absence of a strong theoretical framework to support the use of such data. A key contribution of my book’s analysis of forced-choice self-report survey data is that it presents such a theoretical framework based on recent work in cognitive science and neuroscience. My goal is to provide tools for social scientists to use certain types of extant forced-choice self-report survey data that are not accompanied by psychological measures (Miles et  al. 2019)  to approximate Type I processes.

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The second empirical analysis in this book then advances the literature by developing measures of unconscious schemas. To do so, I perform an experiment using Forster’s Rapid Serial Visual Presentation (RSVP) to empirically examine the effects of conscious and subconscious schemas on moral decision-making reaction times and outcomes. This research contributes in three primary ways: (1) by testing dual-process model casual claims about Type I subconscious moral schemas for the outcomes of moral judgment, (2) by testing causal claims about the absence of Type II conscious reasoning in determining the outcomes of moral judgments, and (3) by utilizing methods designed to isolate the effects of subconscious processes on judgment and decision-making. Contrary to the claims of dual-process models of moral judgment and action, I found that in the case of my experiment, Type I subconscious schemas did not affect moral decision-making while Type II moral deliberation did.

Substantive Scope Key work has demonstrated that the dualism of dual-process models breaks down for various mental processes—such as creativity (Leschziner and Green 2013; Leschziner 2015; Winchester 2016; Cerulo 2018, 2019; Leschziner 2019; Leschziner and Brett 2019; Williams 2020; Bursell and Olsson 2021). However, Lizardo et al. (2016) make a key contribution here, specifying that dual-process models apply under certain scope conditions. Building not only on sociological work on dual-process models (e.g., Vaisey 2009; Vaisey and Lizardo 2010), but also dual-process models in neuroscience (e.g., Greene 2017), this book develops a dual-process model of moral judgment and action. I recognize that dual-process models do not apply in many contexts. However, decades of very strong work convincingly show that dual-process models do apply for moral judgments, moral behaviors, and moral outcomes (Haidt 2001; Vaisey 2009; Vaisey and Lizardo 2010; Vila-Henninger 2015, 2020; for a summary of decades of empirical work in neuroscience, see Greene 2017; Luft 2020; Lockwood et al. 2020). Thus, the dual-process model I develop is limited in its scope to moral judgments and behaviors—and the outcomes of these judgments and behaviors. It is important to note that I use an empirical definition of morality from neuroscience. By “moral judgments” I mean “evaluative judgments of the appropriateness of one’s behavior within the context of socialized perceptions of right and wrong” (Forbes and Grafman 2010: 304). Thus, “morality” and “moral judgments” are not issues of what I think is moral,

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but rather refer to what respondents think of as moral—or what is socially constructed as moral. Furthermore, I am investigating the relationship between moral socialization, judgment, action, and outcomes (Greene 2017; Vila-Henninger 2020). Therefore, work on socialization and attitudes (Vaisey and Lizardo 2016, Kiley and Vaisey 2020; Brett and Miles 2021;  Broć ić and Miles 2021) or socialization and political orientation (Edelmann and Vaisey 2021) is beyond the scope of my analysis and model.

Methodological Scope Over the past several decades, methodological approaches in the sociology of culture and cognition have developed into a thriving literature that employs a diverse range of methods: quantitative analysis with self-report forced-choice survey data (Vaisey 2009, Vaisey and Lizardo 2010; Goldberg 2011; Goldberg and Stein 2018), experimental (Miles 2015; Miles et al. 2019), ethnographic (Ignatow 2009; Winchester 2016; Cerulo 2018), and semi-structured interviews (Vila-Henninger 2018; Leschziner and Brett 2019; Williams 2020). Scholars have also combined methods (Moore 2017; Winchester and Green 2019). Building on Lizardo et al.’s (2016) observation that dual-process models have scope conditions, I argue that these scope conditions apply differently with different dual-process methods. By this I mean that the methods one uses, and how one uses each method, will vary according to the type of dual-process model one uses. For this book, I will use quantitative analysis of forced-choice self-­ report survey data and experimental data. How I use each method (Chaps. 7 and 8) will depend on findings and practices  from cognitive science (Chaps. 3 and 4) and the subsequent dual-process model I build (Chap. 5). I will then discuss this in detail in my analysis (Chaps. 7 and 8) and conclusion (Chap. 9). It is also important to note the limits of different measures. While scholars convincingly demonstrate  that experimental methods best capture Type I processes (Miles et al. 2019), I argue that by applying findings and practices from cognitive science, we can create measures with  certain types of forced-choice self-report survey data that approximate Type I processes but are less accurate than experimental methods. To goal is then to use the findings from studies that use types of forced-choice self-report survey data specified by cognitive science to measure Type I processes in order to help build future experimental studies of automatic Type I processes.

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Outline of Book I begin Chap. 2 by discussing the philosophy behind my approach. This chapter then presents the philosophical foundations of my strategy for building theory by using cognitive science. In Chap. 3, I provide further background for my model by discussing relevant literature that was used to develop dual-process models, as well as the literature on dual-process models in sociology. In Chap. 4, I provide a critique of the foundations of the sociological dual-process model by Stephen Vaisey (Vaisey 2009; Vaisey and Lizardo 2010). I then develop this critique as it applies to work in the subsequent years since Vaisey’s foundational articles. In particular, I argue that there are two problems with this literature: (1) the dichotomy and (2) the data. First, I demonstrate that dual-process models and subsequent work tend to imply a false dichotomy between Type I and Type II processes. Second, I show that the dual-process model literature, and subsequent work in sociology on automatic schemas, are not using the correct data and thus lack construct validity. In Chap. 5, I develop my theory: The Sociological Dual-Process Model of Outcomes (DPMO). In Chap. 6, I provide operationalizations and analysis of the DPMO using forced-choice self-report survey data. In Chap. 7, I provide an analysis of Type I nondeclarative schemas and Type II deliberation using an experiment. In Chap. 8, I conclude by discussing each of my empirical analyses. I then discuss the methodological implications of this book.

Works Cited Abramson, Corey. 2012. “From Either-Or to When and How: A Context-­ Dependent Model of Culture in Action.” Journal for the Theory of Social Behaviour 42(2):155–80. Bourdieu, Pierre. 1984. Distinction: A Social Critique of the Judgement of Taste. Cambridge, Mass: Harvard University Press. Bourdieu, Pierre. 1990. Outline of a Theory of Practice. Cambridge: Cambridge University Press. Bourdieu, Pierre., and Loïc J.  D. Wacquant. 1992. An Invitation to Reflexive Sociology. Chicago: Univ. of Chicago Press. Brekhus, Wayne H. 2015. Culture and Cognition: Patterns in the Social Construction of Reality. Cambridge; Malden (Mass.): Polity.

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Brett, Gordon, and Andrew Miles. 2021. “Who Thinks How? Social Patterns in Reliance on Automatic and Deliberate Cognition.” Sociological Science 8:96–118. Broćić M., and Miles, A. 2021. “College and the “Culture War”: Assessing Higher Education’s Influence on Moral Attitudes”. American Sociological Review 86(5): 856–895. Bursell, Moa, and Filip Olsson. 2021. “Do We Need Dual-Process Theory to Understand Implicit Bias? A Study of the Nature of Implicit Bias against Muslims.” Poetics. Cerulo, Karen A. 2018. “Scents and Sensibility: Olfaction, Sense-Making, and Meaning Attribution.” American Sociological Review 83(2):361–89. Cerulo, Karen A. 2019. “Embodied Cognition: Sociology’s Role in Bridging Mind, Brain, and Body.” In Wayne Brekhus and Gabe Ignatow (eds.), The Oxford Handbook of Cognitive Sociology: pp.  81–100. New  York: Oxford University Press. Cerulo, Karen A., Vanina Leschziner, and Hana Shepherd. 2021. “Rethinking Culture and Cognition.” Annual Review of Sociology 47(1):63–85. Crockett, Molly J. 2013. “Models of Morality.” Trends in Cognitive Sciences 17(8):363–66. Cushman, Fiery. 2013. “Action, Outcome, and Value.” Personality and Social Psychology Review 17(3):273–92. DiMaggio, Paul. 1997. “CULTURE AND COGNITION.” Annual Review of Sociology 23(1). DiMaggio, Paul. 2002. “Why Cognitive (and Cultural) Sociology Needs Cognitive Psychology.” In Karen Cerulo (ed.), Culture in Mind: Toward a Sociology of Culture and Cognition: pp. 274–281. New York: Routledge. Edelmann, Achim, and Stephen Vaisey. 2021. “Gender Differential Effect of College on Socio-political Orientation over the Last 40 Years—a Propensity Score Weighting Approach.” SocArXiv. May 8. doi:10.31235/osf.io/25yux. Forbes, Chad E., and Jordan Grafman. 2010. “The Role of the Human Prefrontal Cortex in Social Cognition and Moral Judgment.” Annual Review of Neuroscience 33(1). Gaddis, S.  M. 2013. “The Influence of Habitus in the Relationship between Cultural Capital and Academic Achievement.” Soc Sci Res 42(1):1–13. doi: https://doi.org/10.1016/j.ssresearch.2012.08.002. Goldberg, Amir. 2011. “Mapping Shared Understandings Using Relational Class Analysis: The Case of the Cultural Omnivore Reexamined.” American Journal of Sociology 116(5):1397–1436. doi: https://doi.org/10.1086/657976. Goldberg, Amir, and Sarah K. Stein. 2018. “Beyond Social Contagion: Associative Diffusion and the Emergence of Cultural Variation.” American Sociological Review 83(5):897–932. Greene, Joshua D. 2017. “The Rat-a-Gorical Imperative: Moral Intuition and the Limits of Affective Learning.” Cognition 167(2):66–77.

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Gross, Neil. 2009. “A Pragmatist Theory of Social Mechanisms.” Amersocirevi American Sociological Review 74(3):358–79. Guetzkow, Josh, and Kathrine Ben-Zvi. 2017. “From Subcultures to Toolkits: Ethnicity and Violence in Israeli Prisons.” Social Forces 95(3):1237–59. Guhin, Jeffrey, Jessica McCrory Calarco, and Cynthia Miller-Idriss. 2021. “Whatever Happened to Socialization?” Annual Review of Sociology 47(1):109–129. Haidt J. 2001. “The Emotional Dog and Its Rational Tail: A Social Intuitionist Approach to Moral Judgment.” Psychological Review 108(4):814–34. Hoffmann, John P. 2014. “Religiousness, Social Networks, Moral Schemas, and Marijuana Use: A Dynamic Dual-Process Model of Culture and Behavior.” Social Forces 93(1). Ignatow, Gabriel. 2007. “Theories of Embodied Knowledge: New Directions for Cultural and Cognitive Sociology?” Journal for the Theory of Social Behaviour 37: 2: 115–135. Ignatow, Gabriel. 2009. “Culture and Embodied Cognition: Moral Discourses in Internet Support Groups for Overeaters.” Social Forces 88(2):643–70. Ignatow, Gabriel. 2019. “Cognitive Sociology and French Psychological Sociology” In Wayne Brekhus and Gabe Ignatow (eds.), The Oxford Handbook of Cognitive Sociology: pp. 137–152. New York: Oxford University Press. Joas, Hans. 1996. The Creativity of Action. Chicago, Ill.: The University of Chicago Press. Kiley K., and Vaisey S. 2020. “Measuring Stability and Change in Personal Culture Using Panel Data.” American Sociological Review 85(3):477–506. Leschziner, Vanina. 2015. At the Chef’s Table: Culinary Creativity in Elite Restaurants. Stanford (CA): Stanford University Press. Leschziner, Vanina. 2019. “Dual-Process Models in Sociology.” In Wayne Brekhus and Gabe Ignatow (eds.), The Oxford Handbook of Cognitive Sociology: pp. 169–191. New York: Oxford University Press. Leschziner, Vanina, and Gordon Brett. 2019. “Beyond Two Minds: Cognitive, Embodied, and Evaluative Processes in Creativity.” Social Psychology Quarterly 82(4): 340–66. Lizardo, O. 2007. “‘Mirror Neurons,’ Collective Objects and the Problem of Transmission: Reconsidering Stephen Turner’s Critique of Practice Theory.” JOURNAL FOR THE THEORY OF SOCIAL BEHAVIOUR 37(3):319–50. Lizardo, Omar. 2004. “The Cognitive Origins of Bourdieu’s Habitus.” Journal for the Theory of Social Behaviour 34(4):375–401. Lizardo, Omar. 2009. “Formalism, Behavioral Realism and the Interdisciplinary Challenge in Sociological Theory.” Journal for the Theory of Social Behaviour 39(1):39–79. Lizardo, Omar. 2017. “Improving Cultural Analysis: Considering Personal Culture in its Declarative and Nondeclarative Modes.” American Sociological Review 82(1):88–115.

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Lizardo, Omar. 2019. “Pierre Bourdieu as Cognitive Sociologist.” In Wayne Brekhus and Gabe Ignatow (eds.), The Oxford Handbook of Cognitive Sociology: pp. 65–80. New York: Oxford University Press. Lizardo, Omar. 2021. “Culture, Cognition, and Internalization”. Sociological Forum. Online First version. Lizardo, Omar, and Michael Strand. 2010. “Skills, Toolkits, Contexts and Institutions: Clarifying the Relationship between Different Approaches to Cognition in Cultural Sociology.” Poetics 38(2):205–28. Lizardo O, Mowry R, Sepulvado B, Stoltz D. S., Taylor, M. A., Van Ness J., and Wood M. 2016. “What Are Dual Process Models? Implications for Cultural Analysis in Sociology.” Sociological Theory 34(4):287–310. Lockwood P.L., Klein-Flugge M.C., Abdurahman A., Crockett M.J., Lockwood P.L., Klein-Flugge M.C., Abdurahman A., Lockwood P.L., and Crockett M.J. 2020. “Model-Free Decision Making Is Prioritized When Learning to Avoid Harming Others.” Proc. Natl. Acad. Sci. U.  S. A.  Proceedings of the National Academy of Sciences of the United States of America 117(44):27719–30. Luft, Aliza. 2020. “Theorizing Moral Cognition: Culture in Action, Situations, and Relationships.” Socius: Sociological Research for a Dynamic World 6:237802312091612. Martin J.L. 2010. “Life’s a Beach but You’re an Ant, and Other Unwelcome News for the Sociology of Culture.” Poetics 38(2):229–44. Martin, John Levi, Desmond, Matthew. 2010. “Political Position and Social Knowledge.” Sociological Forum 25(1):1–26. Mencken, F.  Carson, and Paul Froese. 2017. “Gun Culture in Action.” Social Problems spx040–spx040. doi: https://doi.org/10.1093/socpro/spx040. Miles, Andrew. 2014. “Addressing the Problem of Cultural Anchoring: An Identity-Based Model of Culture in Action.” Social Psychology Quarterly 77: 2: 210–227. Miles, Andrew. 2015. “The (Re)genesis of Values: Examining the Importance of Values for Action.” American Sociological Review 80(4): 680–704. Miles, Andrew. 2019. “An Assessment of Methods for Measuring Automatic Cognition.” In Wayne Brekhus and Gabe Ignatow (eds.), The Oxford Handbook of Cognitive Sociology: pp. 341-366. New York: Oxford University Press  Miles A., Charron-Chenier R., and Schleifer C. 2019. “Measuring Automatic Cognition: Advancing Dual-Process Research in Sociology.” American Sociological Review 84(2):308–33. Mizrachi, Nissim, Israel Drori, and Renee R.  Anspach. 2007. “Repertoires of Trust: The Practice of Trust in a Multinational Organization amid Political Conflict.” American Sociological Review 72(1):143–65. Moore, Rick. 2017. “Fast or Slow: Sociological Implications of Measuring Dual-­ Process Cognition.” Sociological Science 4:196–223. Pagis, Michal, and Erika Summers‐Effler. 2021. “Aesthetic Engagement”. Sociological Forum. Online First edition.

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Parsons, Talcott, and Edward Shils. 1951. Toward a General Theory of Action. New York: Harper Torchbooks. Patterson, Orlando. 2014. “Making Sense of Culture.” Annual Review of Sociology 40:1–30. Rawlings, Craig M., and Clayton Childress. 2021. “Schemas, Interactions, and Objects in Meaning-Making”. Sociological Forum. Online First edition. Rosen E. 2017. “Horizontal Immobility: How Narratives of Neighborhood Violence Shape Housing Decisions.” American Sociological Review 82(2):270–96. Sewell, William H. 2005. Logics of History: Social Theory and Social Transformation. Chicago, IL: University of Chicago Press. Srivastava, Sameer B., and Mahzarin R. Banaji. 2011. “Culture, Cognition, and Collaborative Networks in Organizations.” Amersocirevi American Sociological Review 76(2):207–33. Stoltz, Dustin S., and Omar Lizardo. 2018. “Deliberate Trust and Intuitive Faith: A Dual-Process Model of Reliance.” J Theory Soc Behav Journal for the Theory of Social Behaviour 48(2):230–50. Swidler, Ann. 1986. “Culture in Action: Symbols and Strategies.” Amersocirevi American Sociological Review 51(2):273–86. Swidler, Ann. 2001. Talk of Love: How Culture Matters. Chicago: University of Chicago Press. Swidler, Ann. 2008. “Comment on Stephen Vaiseys Socrates, Skinner, and Aristotle: Three Ways of Thinking About Culture in Action.” SOCF Sociological Forum 23(3):614–18. Turner, Stephen P. 2018. Cognitive Science and the Social: A Primer. New York: Routledge Vaisey, Stephen. 2008a. “Reply to Ann Swidler.” Sociological Forum 23(3):619–22. Vaisey, Stephen. 2008b. “Socrates, Skinner, and Aristotle: Three Ways of Thinking About Culture in Action.” Sociological Forum 23(3):603–13. Vaisey, Stephen. 2009. “Motivation and Justification: A Dual-Process Model of Culture in Action.” AJS; American Journal of Sociology 114(6):1675–1715. doi: https://doi.org/10.1086/597179. Vaisey, Stephen. 2013. “Is interviewing compatible with the dual-process model of culture?” American Journal of Cultural Sociology 2(1):150–58. Vaisey, Stephen, and Margaret Frye. 2019. “The Old One-Two: Preserving Analytical Dualism in Cognitive Sociology.” In Wayne H. Brekhus and Gabe Ignatow (eds.), The Oxford Handbook of Cognitive Sociology: pp. 101–114. New York: Oxford University Press.  Vaisey, Stephen, Lizardo, Omar. 2010. “Can Cultural Worldviews Influence Network Composition?” Social Forces 88(4):1595–1618. Vaisey, Stephen, and Omar Lizardo. 2016. “Cultural Fragmentation or Acquired Dispositions? A New Approach to Accounting for Patterns of Cultural Change.” Socius: Sociological Research for a Dynamic World 2:237802311666972.

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Vanina Leschziner, and Adam Isaiah Green. 2013. “Thinking about Food and Sex: Deliberate Cognition in the Routine Practices of a Field.” Sociological Theory 31(2):116–44. doi: https://doi.org/10.1177/0735275113489806. Vila-Henninger, Luis Antonio. 2015. “Toward Defining the Causal Role of Consciousness: Using Models of Memory and Moral Judgment from Cognitive Neuroscience to Expand the Sociological Dual-Process Model.” Journal for the Theory of Social Behaviour 45(2):238–60. Vila-Henninger, Luis Antonio. 2018. “The Medicinal Cannabis Question: How Actors Legitimate Vote Choice on Medical Marijuana Policy.” The Sociological Quarterly (4):1–24. Vila-Henninger, Luis Antonio. 2020. “A Theory of Popular Political Legitimation: A Dual-Process Model Approach to Legitimation and Political Socialization.” Journal for the Theory of Social Behaviour 50(4):490–515. Wacquant, Loïc. 2016. “A Concise Genealogy and Anatomy of Habitus.” The Sociological Review 64(1):64–72. doi: https://doi.org/10.1111/1467954x.12356. Weber, Max, Hans Gerth, and C. Wright Mills. 1946. From Max Weber: Essays in Sociology. New York: Oxford University Press. Weber, Max. 1946 [1922–3]. “The Social Psychology of the World Religions.” In Hans Gerth and Wright Mills (eds.), From Max Weber: Essays in Sociology: pp. 267–301. New York: Oxford University Press. Williams, Lawrence H. 2020. Thinking through Dilemmas: Schemas, Frames, and Difficult Decisions. New York: Routledge Winchester, Daniel. 2016. “A Hunger for God: Embodied Metaphor as Cultural Cognition in Action.” Social Forces 95(2). Winchester, Daniel, and Kyle D. Green. 2019. “Talking Your Self into It: How and When Accounts Shape Motivation for Action.” Sociological Theory 37(3):257–81.

CHAPTER 2

Conceptual Foundations for Theory-Building

Introduction In the sociology of culture and cognition, there are two general approaches. The first, pioneered by Eviatar Zerubavel (e.g., 1997, 2018), focuses on the social patterning of thought (Brekhus 2015; Brekhus and Ignatow 2019). The second, pioneered by Paul DiMaggio, investigates the mechanisms of thought using an interdisciplinary approach. DiMaggio then builds on Bourdieu by applying cognitive science to investigate the processes through which culture is integrated into cognition (DiMaggio 1997, 2002; Brekhus 2015; Brekhus and Ignatow 2019). Subsequently, Karen Cerulo (Cerulo 2002, 2010; Cerulo et al. 2021) provides an intermediate perspective that investigates how social and cultural factors interact with psychological factors to create social cognition (see also Cerulo 2019; Brekhus and Ignatow 2019). This book builds on DiMaggio’s and Cerulo’s approaches. The dual-­ process model I develop (The Sociological Dual-Process Model of Outcomes, Vila-Henninger 2020) focuses on how sociocultural factors interact with psychological mechanisms through socialization and uses psychology and neuroscience to build a theory of the mechanisms through which culture is processed cognitively. My empirical analysis then develops operationalizations of psychological processes that have further developed through socialization.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 L. A. Vila-Henninger, Socialization, Moral Judgment, and Action, https://doi.org/10.1007/978-3-030-88278-5_2

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By taking this approach, like DiMaggio, I build on the work of Bourdieu and specifically habitus (Bourdieu 1984, 1990). As discussed in Chap. 1, the debate in culture and cognition that has developed from Bourdieu’s work (Strong Practice Theory) has long maintained that cultural ends affect action, but that these ends are subconscious and operate through a dual-process model in which Type I (subconscious) and Type II (conscious) cognition are in conflict (Vaisey 2009, Vaisey and Lizardo 2010). Recent work then counters that Type I and Type II processes are instead dissociated and therefore largely operate independently (Lizardo 2017). This book advances the debate by using neuroscience to develop a dual-process model in which Type I and Type II processes can be independent, can be in conflict, or can work together (Vila-Henninger 2020; Greene 2017). While my approach is based on the work of Bourdieu (1984, 1990), it also has other sociological roots. In this chapter then, I review these conceptual roots. Doing so allows me to address critics of culture and cognition. Some sociologists have criticized the sociological dual-process literature and culture and cognition more broadly—arguing that it makes cultural analysis overly individualistic and ignores social factors (e.g., Swidler 2008; Norton 2014, 2019; Polavieja 2015, 2017; Lembo and Martin 2021). These scholars contend that analysis should focus on the social dynamics that structure cultural meanings and practices rather than on individual cultural socialization—or “enculturation.” Others, however, have sought to move beyond this division by emphasizing the importance of the intersection of cultural context and enculturation for understanding “culture in action” (e.g., Martin 2010; Lizardo and Strand 2010; Abramson 2012; Leschziner and Green 2013). Ultimately, Lizardo (2017) advanced this debate by demonstrating that these different sides “are speaking past” (ibid.: 94) each other and introduced a framework for conceptualizing culture that accounts for social factors and enculturation. In this book, I respond by developing a model of cultural action and cultural socialization in which sociocultural factors interact with psychological factors to shape social cognition and action. I therefore continue the effort to bridge the gap between the sociology of culture and cognition on the one hand and its critics on the other. In doing so, I build on the insights of scholars (e.g., Cerulo 2019, Eck and Turner 2019; Cerulo et  al. 2021) who discuss the usefulness of cognitive science for understanding the interaction of body, mind, and environment in shaping human action.

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To proceed, I outline the conceptual foundations of my theory-­building approach and empirical work in order to position it as fundamentally sociological. First, I discuss the foundations of my approach in the work on Max Weber. Next, I discuss how elements of the Weberian perspective can be applied to use findings from cognitive science. Third, I apply these insights to develop my own conceptual foundations for building theory. I conclude by briefly discussing the connections of my approach to the contemporary culture and cognition literature.

Weberian Foundations For Max Weber—one of the foundational thinkers in Western sociology— the relationship between social structure and mental structures goes back to his definition of the human being. For Weber, there seems to be a feedback loop in which individuals learn certain worldviews and then develop goals that are interpreted according to those worldviews. Cultural frameworks then influence social structure by shaping individual interests and the types of systems of cooperation in which individuals engage. Actors subsequently adjust their worldviews when there is a significant gap between their perceptions and the external environment. Weber’s theory seems to be characterized by the idea that social action is the product of individual interaction and is motivated by interests that are framed in terms of a certain worldview (2002 [1904–5]: 55; 1958 [1913]; 1978 [1922]: 13). Culture, then, mediates between “psychological motivations” and action by providing individuals with a framework that they can use to orient their interests/ends as well as ways to organize their action to achieve their goals  most effectively (2002 [1904–5]: 55). We can see the development of this conceptual framework in Weber’s scholarship. He begins to apply this framework in the Protestant Ethic and the Spirit of Capitalism (PE) (2002 [1904–5]) in an attempt to understand the cultural origins of capitalism by critiquing Karl Marx’s materialism. Weber’s argument is rooted in his observation that a set of cultural practices led to the creation of capitalism as a social system. Weber’s goal, then, is to analyze these cultural foundations (PE: 18–9) by using historical data to construct ideal types of features in protestant dogma that he argued led to capitalism. From this perspective, culture mediates psychological motivations in a way that encourages believers to organize their lives similarly (PE:

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55)—ultimately resulting in the production of social structure. In this particular case, Weber argues that through the establishment of an ethos of religious asceticism oriented toward salvation in the afterlife, the puritan doctrine was motivated to pursue an earthy calling or vocation (PE: 44–5) that demonstrated that Protestants were saved. The result was a “puritan conception of the calling and promotion of an ascetic organization of life…[which] directly influenced the development of the capitalist style of life” (PE: 112). According to Weber, Puritans became the “social carriers” of capitalism (PE: 117) as they spread their faith and consequently their ethos and business practices. For Weber, this ethos then helped to create the essential elements for capitalism, such as surplus labor and capital, and facilitated the rationalization of capitalism by providing individuals in protestant societies with the motivation to facilitate the rationalization of, and reinvestment in, businesses—regardless of class status (PE: 120–4). In his essay “The Social Psychology of the World Religions” (PSWR) (1958 [1913]), Weber continues his critique of the Marxist conception of the relationship between social and mental structures. Weber argues that the Marxist approach to consciousness reduces complex social phenomena to social forces (PSWR: 267–8). Weber expands on this perspective by arguing that for all of the major world religions, a religious-based cultural ethos is seen as a mediating factor that helps to organize individual practices in a community. These practices are then responsive to the demands of the material world but are oriented toward, and interpret, that very world using a particular conceptual framework that is anchored by culturally defined religious goals (PSWR: 270–1). For Weber, the relationship between mental and social structures is a feedback loop: material factors are interpreted through the religious conceptual framework and then enacted through religious ethic. A new generation then responds to religious needs by reinterpreting and recreating the religious framework. This recreation of the framework is then secondarily influenced by economic and political needs (PSWR: 270). Furthermore, for Weber, material and ideal interests—not ideas—govern action. However, ideas and the worldviews they create act as “switchmen” and determine the path in which interests develop (PSWR: 280). Thus, ideas provide a framework for the development and interpretation of interests, which then directly drive interest. It is through this process that the feedback loop between mental and social structures occurs (PSWR: 280–1). The point is that material and ideal interests govern action and that a given doctrine is used to interpret the world to create

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these ends. Religious ideas are used to create systematic interpretations of the world that then define the goals that individuals pursue (PSWR: 280). In this way, believers rationalize their lives to pursue “irrational,” or religiously defined, ends (PSWR: 281). Finally, in Economy and Society (ES) (1922 [1978]), Weber elaborates on this framework further. According to Weber, sociology is concerned with an “interpretive understand of social action,” with “action” being understood as behavior that an “individual attaches a subjective meaning to” (ES: 4). For Weber, meaning is a mix of both conscious and subconscious processes (ES: 5) and can be oriented toward a rational (economic) or irrational (emotional) end (ES: 6). Meaning is understood as the ascribed means or end, so there is a series of factors that affect meaning-­ making and can be understood causally but are not cultural objects themselves—such as physical or psychological stimuli (ES: 7). Causality can be understood in terms of individual pursuit of motives in social contexts (ES: 12, 18) and social phenomena then are the product of individual interaction (ES: 13).

Weberian Foundations Applied to Culture and Cognition For this book, I build on the Weberian foundation outlined above to understand the relationship between mental and social structures, and then follow scholars such as Paul DiMaggio, Karen Cerulo, and Albert Bergesen from the sociology of culture and cognition in taking a heterochthonous approach to theory-building. This means that I will build sociological theory by using findings on cognitive processes from outside of sociology—and from neuroscience and psychology in particular. Weber’s description of cognition as a mix of conscious and unconscious processes that respond to material and psychological needs provides a solid foundation for this heterochthonous theory-building approach. Furthermore, Weber’s argument that psychological factors should be considered when constructing a causal model (1978 [1922]: 13) connects well with DiMaggio’s (2002) discussion of “cognitive sociology” in terms of two major oppositions/dimensions. The first concerns the subject matter/object of study: (1) how we think versus what we think. The second concerns the source of theories of cognition (2) autochthonous versus heterochthonous. Autochthonous approaches only build on findings from

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sociology, while heterochthonous approaches build on findings and theories from outside of sociology—namely cognitive psychology (ibid.: 274–5). One example of heterochthonous theorization is DiMaggio’s (2002) use of literature from psychology that discusses two types of cognition: cold versus hot. Here, “hot” refers to quick, impulsive, and based on stereotypes—and ultimately Type I cognition. “Cold” then refers to reflective and calculating—and ultimately Type II cognition. DiMaggio uses this distinction to discuss how orientations toward action can be structured by two major dimensions which are separate but related: (1) hot versus cool affect and (2) deliberate versus automatic cognition. These conceptual distinctions can then provide a typology of orientations that can be used to synthesize different theoretical perspectives and lead us to an empirical question of how/when actors switch orientations (DiMaggio 2002: 277–8). A key early heterochthonous theorist is Albert Bergesen (2004a, 2004b). For example, Bergesen (2004b) argues that cultural and social variation can be understood in terms of innate, generative, cognitive mechanisms that produce variation through the endless combination and recombination of finite elements (ibid.: 35–6). This thesis stands in direct opposition to traditional sociological theories that posit that human nature and action are determined by internalization/socialization. Adopting a heterochthonous framework, Bergesen uses Noam Chomsky’s theory of the language faculty to critique classic sociological perspectives on cognition.

Theory-Building with Cognitive Science How, then, do we develop a heterochthonous approach to theory-­building that mobilizes cognitive science? First, we must make a key distinction. Throughout its history, there has been confusion in sociology concerning the meaning of the term “theory.” This is due in large part to the fact that the word “theory” has been used to describe two distinct conceptual processes. First, “grand theory,” which is sometimes called “metatheory” (Berger et al. 1989) or “orienting strategy” (Wagner 1984), provides an ontology of the social world that is used in the construction of variables and measures and is often “speculative” in nature. Conversely, “causal models” or “unit theories” explain a particular phenomenon, can be measured empirically (Wagner 1984), and are often constructed inductively using data.

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These two meanings have, not surprisingly, resulted in much confusion as well as a number of divisions in sociology over when and how “theory” should be used. This debate has been subsequently complexified with the increasing use of data that are heterochthonous (DiMaggio 2002) to sociology—and in particular with the use of findings from cognitive science. Lizardo (2009) describes the latter as creating a “major theoretical divide” in sociology between “Formalism” and “Behavioral-Realism” (ibid.: 39). Formalism, or traditional quantitative sociology, attempts to establish the “autonomy of sociology…through the development of formal models of strictly sociological” free from “any sort of reliance on the conceptual baggage and ontological assumptions of other sciences” (ibid.: 40). Conversely, the branch of sociology that uses cognitive science, which Lizardo calls Behavioral-Realism, is characterized as working for “conceptual and empirical integration with those very same disciplines that from the formalist viewpoint are perceived as compromising the integrity of sociology” by “relinquishing the very idea of sociology as an autonomous conceptual edifice” and deriving “concepts and mechanisms” from “biology…or psychology and cognitive science” (ibid.). In other words, while Formalists argue that social phenomena can be understood through inductive, quantitative unit theories, Behavioral-­ Realists work to ground the metatheory of social phenomena by using findings from cognitive science. At the heart of this division, then, are two intersecting issues: the appropriateness of using data that are heterochthonous to sociology and the importance given to each type of theory in conducting research. My perspective echoes a premise that has been voiced by other sociologists. Traditional metatheory is “reasonable but unreliable” and amounts to essentially “armchair theories of how actors use their understandings of the social world” (Martin and Desmond 2010: 1). Given that “sociologists are only beginning to move past” these theories toward the integration of cognitive science (ibid.), there is much work to be done on theoretical approaches to this integration. Furthermore, if this integration is to take place on a broad scale, I argue, along with Lizardo (2009), that it must be done so as to complement Formalist sociology. As previously mentioned, Formalism and Behavioral-Realism differ ontologically as well as in their use of theory. Because ontological beliefs are more subjective and harder to change, my approach seeks to conjoin metatheory and unit theory methodologically to produce findings that can be used to evaluate the effectiveness of using cognitive science—and

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in particular neuroscience and psychology—in sociological research. My approach is therefore a critical review of meta-theoretical claims about cognition using data from cognitive science. My theory-building and analysis build on the work of Bourdieu on habitus and work in sociology on dual-process models (Vaisey 2009, Vaisey and Lizardo 2010; Lizardo et al. 2016; Lizardo 2017) in order to integrate metatheory directly into formal unit theories. Thus, I develop a sociological dual-process model of outcomes (DPMO) as a metatheory using neuroscience and create operationalizations that allow it to be tested empirically. If my unit theory—the  hypotheses derived from the DPMO—produces accurate predictions, then it will have demonstrated that the integration of empirically grounded metatheory with formal predictive models can improve the accuracy of the latter and suggests that sociologists can indeed productively use empirically grounded metatheory. The goal of this analysis is then to address critiques of the unreliability and arbitrariness of metatheory, and especially critiques of metatheory in culture and cognition (Lembo and Martin 2021),  which are shared by Formalists and Behavioral-Realists, as well as concerns by Formalists over the integration of non-sociological data into sociological models. It is then important to note that critics of the culture and cognition literature and heterochthonous metatheory often do not address the theoretical reasoning behind heterochthonous theory-building (Norton 2014, 2019; Polavieja 2015, 2017; Lembo and Martin 2021). Still others base their critiques on a fundamental misrepresentation of the interdisciplinary work taking place in the Sociology of Culture and Cognition (Vaisey 2021) and similarly overlook the theoretical reasoning behind this approach.

Conclusion: Connection to Contemporary Literature My approach builds on the insights of scholars (e.g., Cerulo 2019; Eck and Turner 2019) who discuss the usefulness of cognitive science for understanding the interaction of body, mind, and environment in shaping human action. Here, we need to heed the warning of Leschziner (2019) that classic work in culture and cognition—especially on dual-process models—over-emphasized automatic processes—which then de-­ emphasized the social realm. This is exactly where this book contributes— by building a metatheory based on neuroscience and psychology that does

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not over-emphasize automatic processes and seeks to integrate social factors by developing a model of socialization. In this vein, it is important to recognize that work in sociology on dual-­ process models (e.g., Vaisey 2009,  Vaisey and Lizardo 2010) discussed socialization as a key factor but did not develop a theoretical account of how socialization happens or measures of how it affects action. My dual-­ process model begins to fill these two gaps. Thus, I build on Martin (2019), who emphasizes the need to be able to operationalize habitus. Furthermore, I maintain Vaisey and Frye’s (2019) “analytic dualism” between Type I and Type II cognition, but argue that this dualism is useful under empirical scope conditions (Vila-Henninger 2015, 2020; Lizardo et  al. 2016). In particular, I argue that this dualism should be used strategically and that Type I and Type II are not always independent and are therefore not mutually exclusive. Instead, there is often an interaction between Type I and Type II processes (Vila-Henninger 2015, 2020; Lizardo et al. 2016; Miles et al. 2019) in which Type I and Type II cognition may be in conflict or may share tasks. Thus, I echo Lizardo et  al. (2019) that neuroscience contributes to the sociology of culture—and the question of causality in culture—but that to answer this question we can productively use cognitive science to develop ontological and epistemological views.

Works Cited Abramson, Corey. 2012. “From Either-Or to When and How: A Context-­ Dependent Model of Culture in Action.” Journal for the Theory of Social Behaviour 42(2):155–80. Berger, Joseph., David G. Wagner, and Morris Zeldtich. 1989. “Theory Growth, Social Processes, and Metatheory.” Theory Building in Sociology: Assessing Theoretical Cumulation / Jonathan H. Turner, Editor. Bergesen, Albert J. 2004a. “Chomsky versus Mead.” Sociological Theory 22(3):357–70. Bergesen, Albert J. 2004b. “Durkheim’s Theory of Mental Categories: A Review of the Evidence.” Annurevisoci Annual Review of Sociology 30:395–408. Bourdieu, Pierre. 1984. Distinction: A Social Critique of the Judgement of Taste. Cambridge, Mass: Harvard University Press. Bourdieu, Pierre. 1990. Outline of a Theory of Practice. Cambridge: Cambridge University Press. Brekhus, Wayne H. 2015. Culture and Cognition: Patterns in the Social Construction of Reality. Cambridge; Malden (Mass.): Polity.

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Brekhus, Wayne, and Gabe Ignatow. 2019. The Oxford Handbook of Cognitive Sociology. New York: Oxford University Press. Cerulo, Karen A. 2002. Culture in Mind: Toward a Sociology of Culture and Cognition. New York: Routledge. Cerulo, Karen A. 2010. “Mining the Intersections of Cognitive Sociology and Neuroscience.” Poetics. 38(2):115. Cerulo, Karen A. 2019. “Embodied Cognition: Sociology’s Role in Bridging Mind, Brain, and Body.” In Wayne Brekhus and Gabe Ignatow (eds.), The Oxford Handbook of Cognitive Sociology: pp.  81–100. New  York: Oxford University Press. Cerulo, Karen A., Vanina Leschziner, and Hana Shepherd. 2021. “Rethinking Culture and Cognition”. Annual Review of Sociology 47(1):63–85. DiMaggio, Paul. 1997. “Culture and Cognition.” Annual Review of Sociology 23(1). Eck, David, and Stephen Turner. 2019. “Cognitive Science and Social” In Wayne Brekhus and Gabe Ignatow (eds.), The Oxford Handbook of Cognitive Sociology: pp. 153–168. New York: Oxford University Press. Greene, Joshua D. 2017. “The Rat-a-Gorical Imperative: Moral Intuition and the Limits of Affective Learning.” Cognition 167(2):66–77. Javier G. Polavieja. 2017. “Culture as a Random Treatment: A Reply to Chou.” American Sociological Review. Lembo, Alessandra, and John Levi Martin. 2021. “The structure of cultural experience”. Poetics. Online First edition. Leschziner, Vanina. 2019. “Dual-Process Models in Sociology.” In Wayne Brekhus and Gabe Ignatow (eds.), The Oxford Handbook of Cognitive Sociology: pp. 169–191. New York: Oxford University Press. Lizardo O., Mowry R., Sepulvado B., Stoltz D.S., Taylor M.A., Van Ness J., and Wood M. 2016. “What Are Dual Process Models? Implications for Cultural Analysis in Sociology.” Theory Sociological Theory 34(4):287–310. Lizardo, Omar. 2009. “Formalism, Behavioral Realism and the Interdisciplinary Challenge in Sociological Theory.” Journal for the Theory of Social Behaviour 39(1):39–79. Lizardo, Omar, Brandon Sepulvado, Dustin S.  Stoltz, and Marshall A.  Taylor. 2019. “What Can Cognitive Neuroscience Do for Cultural Sociology?” American Journal of Cultural Sociology 8(1):3–28. Martin, J.L. 2010. “Life’s a Beach but You’re an Ant, and Other Unwelcome News for the Sociology of Culture.” Poetics 38(2):229–44. Martin, John Levi. 2019. “Can Carnal Sociology Bring Together Body and Soul?: Or, Who’s Afraid of Christian Wolff?” In Wayne Brekhus and Gabe Ignatow (eds.), The Oxford Handbook of Cognitive Sociology: pp. 115–136. New York: Oxford University Press Martin, John Levi, Desmond, Matthew. 2010. “Political Position and Social Knowledge.” Sociological Forum 25(1):1–26.

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Miles A., Charron-Chenier R., and Schleifer C. 2019. “Measuring Automatic Cognition: Advancing Dual-Process Research in Sociology.” American Sociological Review 84(2):308–33. Norton, Matthew. 2014. “Mechanisms and Meaning Structures.” Sociological Theory 32(2):162–87. Norton, Matthew. 2019. “Cultural Sociology Meets the Cognitive Wild: Advantages of the Distributed Cognition Framework for Analyzing the Intersection of Culture and Cognition.” American Journal of Cultural Sociology 8(1):45–62. Omar Lizardo. 2017. “Improving Cultural Analysis: Considering Personal Culture in its Declarative and Nondeclarative Modes.” American Sociological Review 82(1):88–115. Paul DiMaggio. 2002. “Why Cognitive (and Cultural) Sociology Needs Cognitive Psychology.” Culture in Mind: Toward a Sociology of Culture and Cognition 274–81. Polavieja, Javier G. 2015. “Capturing Culture.” Am Sociol Rev American Sociological Review 80(1):166–91. Swidler, Ann. 2008. “Comment on Stephen Vaiseys Socrates, Skinner, and Aristotle: Three Ways of Thinking About Culture in Action.” SOCF Sociological Forum 23(3):614–18. Vaisey, Stephen. 2009. “Motivation and Justification: A Dual-Process Model of Culture in Action.” AJS; American Journal of Sociology 114(6):1675–1715. Vaisey, Stephen. 2021. “Welcome to the Real World: Escaping the Sociology of Culture and Cognition”. Sociological Forum. Online First version. Vaisey, Stephen and Omar Lizardo. 2010. “Can Cultural Worldviews Influence Network Composition?” Social Forces 88(4):1595–1618. Vaisey, Stephen, and Margaret Frye. 2019. “The Old One-Two: Preserving Analytical Dualism in Cognitive Sociology.” In Wayne H. Brekhus and Gabe Ignatow (eds.), The Oxford Handbook of Cognitive Sociology: pp.  101–114. New York: Oxford University Press. Vanina Leschziner, and Adam Isaiah Green. 2013. “Thinking about Food and Sex: Deliberate Cognition in the Routine Practices of a Field.” Sociological Theory 31(2):116–44. Vila-Henninger, Luis Antonio. 2015. “Toward Defining the Causal Role of Consciousness: Using Models of Memory and Moral Judgment from Cognitive Neuroscience to Expand the Sociological Dual-Process Model.” Journal for the Theory of Social Behaviour 45(2):238–60. Vila-Henninger, Luis Antonio. 2020. “A Theory of Popular Political Legitimation: A Dual-Process Model Approach to Legitimation and Political Socialization.” Journal for the Theory of Social Behaviour 50(4):490–515. Wagner, David G. 1984. The Growth of Sociological Theories. Beverly Hills: Sage Publications.

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Weber, Max. 1978. Economy and Society. an Outline of Interpretive Sociology. Berkeley: University of California Press. Weber, Max. 2002. The Protestant Ethic and the Spirit of Capitalism. Los Angeles: Roxbury. Weber, Max. 1958 [1913]. “The Social Psychology of the World Religions.” In H.H. Gerth and C. Wright Mills (eds.). Pp. 267–301. From Max Weber: Essays in Sociology. New York: Oxford. Zerubavel, Eviatar. 1997. Social Mindscapes: An Invitation to Cognitive Sociology. Cambridge, MA: Harvard University Press. Zerubavel, Eviatar. 2018. Taken for Granted: The Remarkable Power of the Unremarkable.

CHAPTER 3

Background: Models of Action and Socialization

Introduction The question of causality in culture is the central theme of this book. Therefore, this book asks: How does culture affect action? As discussed in the introduction, this has two primary elements: (1) Models of Action and (2) Socialization. This book then develops a dual-process model that accounts for socialization in such a way that can be linked to action via moral judgment. Thus, in this chapter, I provide a background of the literature in the sociology of culture and related areas on (1) Models of Action and (2) Socialization. This will then set the stage for Chap. 4, which will critique extant Models of Action and Socialization using cognitive science.

Models of Action Overview of Strong Practice Theory Beginning in the 1970s, sociologists began to take serious issue with the cultural theory of Max Weber, which had been interpreted by Parsons (e.g., Parsons and Shils 1951) and Geertz (1973). The result was the development of a school of thought in which social action can be understood by analyzing the mechanisms behind everyday action (for a summary, see Lizardo and Strand 2010). From this tradition, a literature © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 L. A. Vila-Henninger, Socialization, Moral Judgment, and Action, https://doi.org/10.1007/978-3-030-88278-5_3

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dubbed “Strong Practice Theory” (Lizardo and Strand 2010) emerged, which addresses the debate over causality in culture that has been framed in terms of the primacy of cultural ends (intuitions, goals, values) versus cultural means (skills, resources, toolkits). Strong Practice Theory generally argues that cultural ends do not need to be consciously coherent because they are largely subconsciously coherent. It is then primarily via subconscious embodied practical schemas that an actor’s behavior is affected by cultural ends (Bourdieu 1984, 1990; Bourdieu and Wacquant 1992; Ignatow 2007, 2009, 2019; Lizardo 2004, 2007, 2009, 2017, 2019; Martin and Desmond 2010; Vaisey 2008a, 2008b, 2009, 2013; Vaisey and Lizardo 2010; Vaisey and Frye 2019). Within Strong Practice Theory, Stephen Vaisey and others have worked to develop the “sociological dual-process model” as a theoretical framework for analyzing the effects that cultural ends have on behavior. This model explicitly synthesizes accounts of cognition from Pierre Bourdieu (e.g., 1984) and Anthony Giddens (1984), with a theory of mental systems from moral psychology (Haidt 2001). Synthesizing Bourdieu and Giddens, the sociological dual-process model argues that social structure is created/reproduced by motivations that are socially conditioned, subconscious, and embodied (“practical consciousness”). Reappropriating Jonathan Haidt’s (2001) “Social Intuitionist” model, Vaisey argues that moral judgments are largely caused by subconscious intuitions. “Discursive consciousness,” which is traditionally linked to rationality, is understood as having little causal impact on action and is instead conceptualized as creating post hoc discursive justifications for action. The sociological dual-process model stems from Bourdieu’s habitus. Bourdieu explicitly addresses critiques of the habitus by arguing that consciousness can override dispositions or can regulate them by pitting them against one another (Bourdieu and Wacquant 1992: 136). He then extends this description by claiming that “agents become something like ‘subjects’ only to the extent that they consciously master the relation they entertain with their dispositions” (Bourdieu and Wacquant 1992: 137). This characterization complements his description of the habitus and its role in determining action by creating a role for consciousness to regulate unconscious dispositions as well as override them. However, Bourdieu does not theorize how or when either of these functions of consciousness occur in social life.

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This thread carries over to the work of Vaisey, who argues that discursive consciousness “can, under the right conditions, override the habitus” (Vaisey 2009: 610). However, Vaisey posits that actors are “primarily driven by deeply internalized schematic processes” (Vaisey 2009: 1687). He uses Haidt’s metaphor of a rider on an elephant and contends that the “rider,” or discursive consciousness, “can slowly train the elephant [practical consciousness] over time or perhaps trick it into going a different way” (Vaisey 2009: 1683). The Sociological Dual-Process Model and the Means/Ends Debate To proceed, we need more background on Stephen Vaisey’s (Vaisey 2009; Vaisey 2010) dual-process model—as this model serves as a foundational element of the debate about causal processes in culture and is a reference point for subsequent dual-process models (Hoffmann 2014; Miles 2014; Vila-Henninger 2015, 2020; Lizardo 2017; Miles et  al. 2019; Luft 2020). Stephen Vaisey’s “dual-process model” synthesizes his interpretation of two well-established cultural models in sociology using findings from cognitive science. The first is the “discursive” model, which takes a justificatory approach by seeing actors as using cultural frameworks that best justify their actions. The second, then, is the motivational approach, in which actors internalize moral schemas that then play a role in motivating their actions. Drawing on findings from cognitive science, Vaisey argues that actors are endowed with cultural capacities that allow them to make use of culture in both of these ways. Vaisey’s dual-process model developed as part of the means/ends debate in the sociology of culture. To understand Vaisey’s dual-process model, we have to start by understanding Ann Swidler’s (1986, 2001, 2008) theory of culture—which is foundational for the “means” perspective—because it is the primary framework against which Vaisey argues. For Ann Swidler (1986, 2001, 2008), and especially in her 2001 book Talk of Love (TOL), culture consists of different skill sets that need to be performed to create meanings and therefore can be more or less effective depending on the skill of the practitioner (TOL: 24–5, 133). The cultural repertoire of each person is organized around a core set of problems in a person’s life that “provide contexts within which particular pieces of

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culture make sense” (TOL: 25). Cultural frameworks are subsequently applied to different situations in a person’s life, with each situation being an “independent [but]…potentially related, scene” (TOL: 34). Swidler then analyzes how much culture people use and how they use it (TOL: 43) through interview research, which she argues helps best capture these two phenomena (TOL: 222). Responding to Weber, who argues that coherent and rationally organized cultural ends motivate action, Swidler investigates how much people use culture and how coherent the culture they use is (TOL: 69). After reviewing types of cultural tools (TOL: 71–79), Swidler contends that instead of shaping action by influencing values or other cultural ends, culture facilitates action by providing pre-formed “strategies of action” that help people to coordinate collective action (TOL: 82). The argument, then, is that while culture plays a role in action, it does so through “strategies of action.” These strategies of action are then used primarily by actors to react to situations and solve problems (TOL: 83). For Swidler, the emphasis is on action as a response to social factors, which uses broader strategies of actions that are useful in a given situation. The rate of change of these strategies and their coherence is then determined by the stability in the actor’s environment. If the actor’s life is relatively predictable and her/his strategies are successful in providing effective responses to problems that arise, their strategies of action become habitual and stable. However, if structural conditions fluctuate and old strategies of action are no longer effective in providing solutions, the actor must search for and form, in a more cognizant manner, new strategies of action (TOL: 94). Yet, the ontology of these strategies and their relationship to action remains the same: strategies, which are more or less salient, are used by actors primarily to respond to problems, which are more or less consistent, through the use of cultural repertoires—which include values. The cultural repertoire becomes an intervening factor between strategies of action, which are employed in response to environmental factors, and an agent’s actions (TOL: 187). Values, then, “are not the reason why a person develops one strategy rather than another” (TOL: 86), they are merely used to “orient important choices within that strategy” (ibid.). These responses can then be structured by institutional forces and tailored to specific organizational contexts (TOL: 179) by creating a salient set of problems for which the actor is forced to develop a coherent strategy of action (TOL: 178, 202).

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Vaisey’s dual-process model starts with a critique of Swidler (1986, 2001, 2008) and other similar theories, which he characterizes as “the justificatory view.” Vaisey’s concern is with what he claims is Swidler’s dismissal of respondents’ “contradictory or incoherent accounts” as motivating their action, which she describes instead as being driven by social factors (Vaisey 2009: 1680). It is in response to this characterization that Vaisey argues that a “practice” model of cognition can be integrated to help explain how values can both motivate actions and not be coherently articulated by respondents. Vaisey (2009) argues that Swidler and the justificatory theorists assume that there is only one model of cognition—the discursive model—in which actors consciously perceive the world, calculate actions, and express themselves. However, a parallel tradition asserts that consciousness is “automatic” and that culture is internalized through social conditioning (Vaisey 2009: 1681). Vaisey argues that agents have both cognitive processes. He does so by drawing on findings from cognitive science which supports the idea of a subconscious cognitive process that directs habitual practice and is responsible for a majority of action, and then a conscious process that can respond with a degree of reflexivity and purpose to environmental factors (Vaisey 2009: 1684). Furthermore, it is in the practical consciousness, or subconscious process, that values or beliefs are inculcated—which lead agents to act out these values unreflexively (ibid.). These values, patterned as culturally bounded, yet actor-specific schemas “automatically generate different evaluative and behavioral responses according to the interaction of the neural connections and the nature of the inputs” (Vaisey 2009: 1687). Thus, there is a “dual-process model” with both automatic and deliberative cognition. Vaisey argues that because there are two relatively independent cognitive processes, one of which operates subconsciously to guide habitual action, interviews are unable to measure practical consciousness. He responds to this challenge by creating “forced-choice surveys” which he asserts force respondents to “draw disproportionately on practical consciousness” (Vaisey 2009: 1688). To test his model, Vaisey uses the two-wave National Study of Youth and Religion (NSYR) survey data on youth religious attitudes, collected in 2002 and 2005 (Vaisey 2009: 1690), as well as in-depth follow-up interviews of a sample of these respondents from each wave. His model produces two hypotheses (1690): (1) that because conscious cognition is not strongly involved in everyday moral decision-making, interview responses

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will not provide a coherent explanation for moral decision-making; (2) practical consciousness/habitus will provide a predictive measure for moral decision-making. Vaisey uses Bellah et al.’s (1985) four-part moral schema to create the survey questions (Vaisey 2009: 1691) and a three-­ part coding for his interview data. Vaisey (Vaisey 2009: 1694–5, 1698) finds that the interview data support Swidler’s claims that conscious, discursive moral reflection does not provide adequate justification for a respondent’s actions and is often contradictory or illogical. With the use of survey data which forced respondents to characterize their moral framework using an adaptation of Bellah et al.’s (1985) four moral categories, Vaisey also finds that “the choice of moral script in 2002 is a very good overall predictor of behavior in 2005, even controlling for network characteristics, religious participation, and demographic factors” (Vaisey 2009: 1703). This finding then supports Vaisey’s second hypothesis about the influence of internalized values on action. Vaisey concludes that surveys are important tools for measuring how meaning affects action, but that interviews are also important due to their ability to help researchers understand “how people ‘make sense’ of the world to each other and to themselves in the face of an inquisitive questioner” (Vaisey 2009: 1705). Critical Perspectives Critiques of Vaisey’s (2009) dual-process model have emerged in the years following its publication. These critical perspectives help to temper Vaisey’s (2009) claim that reasoning has little or no role in determining behavior. These perspectives also challenge some of the assumptions made by Vaisey’s (e.g., 2009) model and methodological claims. For example, Vila-­ Henninger (2015) used findings from neuroscience that show that goal-­ oriented reasoning is an important factor in shaping action. Vila-Henninger (2015) also demonstrated that Type I (automatic) and Type II (deliberative/discursive) processes can, and often do, interact. This then calls into question Strong Practice Theory’s dichotomy between Type I and Type II processes. Vila-Henninger (2015) and Miles et  al. (2019) also demonstrate that Vaisey’s (2009) claims about forced-choice self-report forced-­ choice attitudinal survey data as measuring practical consciousness are not supported empirically. Instead, they show that these responses are actually a better measure of the interaction between Type I and Type II processes or of Type II processes alone.

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Further work shows ways that Strong Practice Theory’s dichotomy breaks down in certain circumstances—for example, for certain cognitive processes such as creativity, as well as because of contextual factors (Abramson 2012; Leschziner and Green 2013; Leschziner 2015; VilaHenninger 2015, 2020; Winchester 2016; Moore 2017; Cerulo 2018, 2019; Leschziner 2019; Leschziner and Brett 2019; Bursell and Olsson 2021; Williams 2021). Crucially, Lizardo (2017) contends that Type I and Type II processes are dissociable and thus relatively independent rather than in conflict—as Haidt (2001) and Vaisey (2009, 2010) suggest. A key gap, then, is that while the literature acknowledges that conscious cognition can override subconscious dispositions or impulses, or can directly affect decision-making, neither Strong Practice Theory (Ignatow 2007, 2009, 2019; Vaisey, 2013, 2010; Vaisey and Frye 2019) nor critical perspectives have developed a formal model using cognitive science to address when and how these two phenomena occur. The closest sociologists have come to filling these gaps is work that specifies conditions under which it is plausible that discursive consciousness overrides practical consciousness (Lizardo and Strand 2010; Abramson 2012; Vila-Henninger 2015; Lizardo et  al. 2016; Miles et  al. 2019; Vaisey and Frye 2019). Furthermore, except for Ignatow (2007, 2009) and Vila-Henninger (2015, 2020), this body of literature does not address how these two forms of cognition interact to affect decision-making.

Socialization The second question this book addresses is that of socialization. What are the processes of socialization through which individuals internalize culture? By outlining the literature for understanding this question, we can then proceed to build a model of socialization that is connected to action (Chap. 5). I therefore review the following relevant literatures: (1) Motivated Reasoning and Prior Beliefs, (2) Moral Foundations Theory (MFT), (3) Terror Management Theory/Systems Justification, (4) Theories of Political Socialization, and (5) the Sociology of Culture. Motivated Reasoning and Prior Beliefs The Motivated Reasoning and Prior Beliefs literature is distinct in its focus on political rationalization as a psychological phenomenon that is connected to socialization. Since the 1970s, models of political reasoning

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have focused on the mechanisms—such as biases (Kahneman and Tversky 1972) and heuristics (Tversky and Kahneman 1974)—that shape information processing in ways that diverge from classic rational choice models (Bartels 2002; Lau and Redlawsk 2006; Baldassarri 2012; Lodge and Taber 2013; Kraft et  al. 2015; Lau et  al. 2018). A central tenet of this research is that the biases and heuristics used in initial voter decision-­ making or attitude formation are either generated in part by prior beliefs and expectations (e.g., Baldassarri 2012: 216) or drive actors to attempt to maintain these prior beliefs (e.g., Lodge and Taber, 2013). Much of this work has taken place on “motivated reasoning.” In this literature, two primary motives for political reasoning have been found: (1) establishing the accuracy of the actor’s conclusion and (2) reaffirming “prior beliefs”—such as views, identities, and expectations (e.g., Kunda 1990; Taber and Lodge 2006; for a summary, see Leeper and Slothuus 2014). Regarding this second motive, partisan prior beliefs have been thoroughly established as a mechanism for driving—and biasing—voter information processing (e.g., Brooks and Manza 2013; Lodge and Taber 2013; Bolsen and Druckman 2018; for a summary of foundational work, see Taber and Lodge 2006). These partisan prior beliefs and subsequent biases are “driven by automatic affective processes” (Lodge and Taber 2013: 150) that then structure information processing and rationalization (Lodge and Taber 2013: 150). Furthermore, there is a rich literature on the importance of prior beliefs and expectations in shaping other elements of reasoning—such as citizens’ political rationalizations (Taber and Lodge 2006; Lodge and Taber 2013). This literature defines political rationalization as post hoc justification that draws upon prior beliefs and expectations (Achen and Bartels 2016). To understand the role of prior beliefs in rationalization, scholars use formal models of reasoning (e.g., Feldman and Conover 1983; Rahn et al. 1994) that sometimes see these beliefs as “priors” in Bayesian updating processes (e.g., Achen and Bartels 2006, 2016). While rationalization is conceptualized by some as part of attitude formation (Gaines et  al. 2007), most scholars portray it simply as a way to help the actor “sound rational”— thus saving face in a given social context (Achen and Bartels 2016)—and therefore creating an account of rationalization that is parallel to the account from dual-process models of moral judgment (Haidt 2001; Vaisey 2009; Vaisey 2010). Analogous to the motivated reasoning scholarship, work on political rationalization identifies accuracy (Achen and Bartels

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2006) and prior belief reaffirmation (Feldman and Conover 1983; Conover and Feldman 1989) as primary motivators. Research has demonstrated that “group loyalties and partisan biases” (Achen and Bartels 2016: 296) shape the prior beliefs that individuals adopt—as well as how they use these beliefs in their political rationalization. Reaffirming work on the importance of partisanship as a motivating factor (Taber and Lodge 2006; Brooks and Manza 2013; Lodge and Taber 2013; Leeper and Slothuus 2014; Bolsen and Druckman 2018), scholars argue that partisan allegiance motivates actors to use their prior partisan beliefs and expectations to rationalize their political activity so that it aligns with their party’s position or discourse (Achen and Bartels, 2016). This provides the insight that partisans are not simply motivated to use rationalization to defend their position, but to defend their position so that it aligns with that of their affiliated party or political group/allegiance. As Brooks and Manza (2013) point out, a gap in the heuristics and biases literature concerns the prior beliefs that motivate and generate these information processing mechanisms. A key parallel comes from the sociology of culture, which identifies schemas, or “largely unconscious networks of neural associations that facilitate perception, interpretation, and action” (Vaisey 2009: 1686), as part of automatic processes connected to evaluation and decision-making. Brooks and Manza (2013) then acknowledge the importance of integrating the dual-process model into work on biases and heuristics, specifically by addressing the “challenge of engaging points of overlap versus divergence with the heuristics and biases tradition” (ibid.: 745). Moral Foundations Theory Moral Foundations Theory (MFT) and the Motivated Reasoning and Prior Beliefs literatures have been recognized as part of the same theoretical project (Kahneman and Sunstein 2007). However, MFT offers a unique perspective that distinguishes itself from most of the Motivated Reasoning and Prior Beliefs research and offers key insights into socialization. To summarize, Moral Foundations Theory (MFT) provides an account in which automatic moral intuitions drive political allegiance, which then allow actors to resonate with collective ideological narratives that they use to justify their political activity (e.g., Haidt et  al. 2009; Graham et  al. 2009; Haidt 2012; Graham et al. 2013).

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MFT asserts that there is a divide in the innate intuitions of humans: “universalism” versus “parochialism” (for a summary, see Waytz et  al. 2019). The key here is that “[u]niversalism refers to moral regard directed toward more socially distant and structurally looser targets, relative to socially closer and structurally tighter targets. Parochialism refers to moral regard directed toward socially closer and structurally tighter targets, relative to socially more distant and structurally looser targets” (Waytz et al. 2019: 2). This distinction has developed from years of empirical work in moral and political psychology (e.g., Singer 1981; Deutsch 1990; Jost et al. 2009; Graham et al. 2009; Waytz et al. 2019). For MFT (Haidt 2012), each ideological perspective is based on a “most sacred value” that anchors its collective ideological moral narrative and is the most central principle for those who share that ideological perspective (Tetlock et  al. 2000: 853; Tetlock 2003; Graham and Haidt 2012: 14; Haidt 2012: 345, 364). Most sacred values then serve as the foundation for ideological conceptions of liberty (“positive” vs. “negative” [Berlin, 1969]) but are distinct from these conceptions. Furthermore, these collective ideological narratives shape individuals’ political identity and socialization (Smith 2003; Haidt et al. 2009; Haidt 2012: 345). Centrally, actors draw upon most sacred values and other elements of collective ideological narratives to create post hoc ideological reasoning that justifies their political activity (Nisbett and Wilson 1977; Haidt et al. 2009: 111; Haidt 2012). From this perspective, most sacred values bridge moral intuitions and individual-level post hoc political reasoning by serving as central elements of a collective ideological narrative (Haidt 2001; Haidt et al. 2009: 111; Haidt 2012: 364–5; Feinberg and Willer 2015). In this model, explicit post hoc reasoning is important because it indicates the activation of individual-level moral intuitions that actors likely used to make initial political judgments. This same post hoc reasoning also reaffirms an actor’s commitment to a political affiliation and its policy positions (Haidt 2012). Subsequently, ideological rationalizations convince others and spread moral political judgments across society (Haidt et  al. 2009: 111). It is important to note that there are ongoing empirical debates about whether these moral intuitions are innate or are acquired through socialization (Smith et al. 2017).

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Terror Management Theory/Systems Justification Terror Management Theory builds on the psychological perspectives on rationalization and socialization by understanding this phenomenon in terms of political justification. This perspective proposes that ideology and political systems are designed to manage and minimize existential threats that humans face (for a summary, see Jost et al. 2009). Actors are then motivated by the psychological need to minimize threats (Jost et al. 2004, 2009). This literature has empirically linked these motives to political ideology and political legitimations (for a full model of motives in Terror Management Theory, see Jost et al. 2009: 319). System Justification Theory emerged and developed in tandem with Terror Management Theory, positing that actors who are motivated by the desire to preserve the status quo are driven by an aversion to threats posed by the disintegration of the social system (for a review, see Jost and Banaji 1994; Jost et al. 2009, 2019). Actors then engage in political justification as a way to avoid, minimize, or eliminate threats that the status quo faces. This theory posits that actors acquire beliefs that motivate them to legitimate political systems through socialization. The key here is that actors are motivated by a sense of threat to legitimate extant political systems or activities that reaffirm the status quo (for a review, see Jost et al. 2009, 2019). Theories of Political Socialization Next, I review work in political science and sociology on political socialization (see also Haegel 2020). A starting place is the “socialization hypothesis” in political science, which argues that actors acquire (often partisan) values through political experiences that are fundamentally structured by institutional context. The debate is then over the role that experience beyond childhood has in continuing to develop value orientations (Almond and Verba 1963; Easton 1965; Parsons 1969; Inglehart 1977, 1997; Almond and Powell 1978; Abramson and Inglehart 1995; Norris 1999; Dalton 2014: 89, 97) or broader political beliefs (Dalton 1980). Actors then also continually draw upon their developing political experiences to make judgments of political support (Easton 1975) as well as the performance of the regime (Norris 1999: 231)—though this may be mediated by the visibility of policy in citizens’ experiences (Soss and Schram 2007: 122).

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Furthermore, there is debate over the degree of agency and political deliberation involved in childhood political socialization, with some arguing for socialization as happening “largely unconsciously and without choice during childhood” (Mishler and Rose 2001: 80) and others finding that children perceive their parents’ partisan affiliation and then choose whether or not to adopt this partisan identity (Ojeda and Hatemi 2015). Easton and Dennis (1967) seem to provide a framework that encompasses both of these perspectives by arguing that through a variety of processes children internalize political norms and values—which then generate political dispositions and broader patterns of political conduct. There is further debate about whether or not political socialization is continuous or happens “episodically” through the experience of key “exogenous political events” (Sears and Valentino 1997). Work has also demonstrated that children affect the political socialization of parents (Dahlgaard 2018). Furthermore, two key perspectives employ the concept of “habitus”— and thus respond to the question of whether the effects of socialization are dispositional. For Pierre Bourdieu (Bourdieu 1984: 409–435), political socialization occurs along class lines and leads to different types of political cognition. Those whose economic existence is plagued with concerns about the material conditions of existence tend to misrecognize political issues as moral or practical issues and their response is generated by their class habitus. Those who are higher on the “hierarchy of incomes and qualifications” (Bourdieu 1984: 427) are more likely to learn political principles and then use these principles either to match a stance on a political issue with a partisan stance or to generate a political judgment based on individual deliberation. Elias (1996) provides another important perspective, in which habitus—in this sense defined as “embodied social learning” (Dunning and Mennell 1998; Delmotte et al. 2017: 230)—and group identity are slowly socially acquired. These processes then produce a “drag effect” in which actors respond attitudinally and affectively to new social and political factors using a habitus and social identity formed in earlier life experience (Delmotte et al. 2017). Finally, there is an important tradition of the use of psychological models to understand political socialization (e.g., Cook 1985). There has also been a key development in European studies in which scholars use qualitative research to understand democratic linkages (Duchesne et  al. 2013; Van Ingelgom 2014)—which can help explain democratic linkages that

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have been documented using quantitative research (e.g., Hooghe and Stiers 2016; Grasso et al. 2019). The Sociology of Culture This literature offers a distinctly sociological perspective on social justification and socialization that builds on the psychological literature. Strong Practice Theory, for example, largely dismisses legitimation as a way for actors to save face and “sound rational.” Such dismissals focus on the relationship between rationalization/social justification and individual behavior. The argument is that these rationalizations retrospectively justify behavior that is driven by automatic processes that the individual does not understand or of which the individual is not aware. Thus, rationalization/ social justification has little or no role in driving behavior (for summaries, see Vaisey 2009, 2010; for a similar argument, see Achen and Bartels 2016). However, the gap here is that these theories of rationalization are not connected to models of socialization. We can see this for example in Vaisey’s (2009, 2010) sociological dual-process model—which extends Jonathan Haidt’s (2001) dual-process model from moral psychology. Vaisey’s (2009, 2010) model posits that actors socially learn schemas that motivate action through Type I (automatic) cognitive processes. Actors then use Type II (deliberative) cognition to provide socially desirable post hoc rationalizations of these actions. As with other perspectives discussed in this chapter, socialization is a central feature of this model, but the model itself does not provide any theorization of how socialization is linked to rationalization. Furthermore, this perspective does not theorize rationalization or socialization. More broadly, the “Culture and Cognition” literature has long sought to disentangle and define the role of cognition in cultural socialization, or “enculturation”—defined as the storage, processing, and use of culture by individuals (Lizardo et al. 2016: 292; Lizardo 2017: 90–1; for reviews, see DiMaggio 1997, 2002; Patterson 2014; Brekhus 2015; Brekhus and Ignatow 2019; Mohr et al. 2020). Culture and Cognition scholars contribute by building on—or responding to—Vaisey’s dual-process model to refine our understanding of the processes through which various elements of culture affect action (e.g., Martin 2010; Martin and Desmond 2010; Beyerlein and Vaisey 2013; Vaisey 2013; Miles 2014, 2015; Vila-­ Henninger 2015; Lizardo et al. 2016; Winchester 2016; Lizardo 2017).

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Lizardo et  al. (2016) contribute to this literature by outlining the “Dual-Process Framework” (DPF). The argument is that cognitive science and neuroscience have established three general guidelines for understanding the role that cognition plays in cultural socialization. First, there are two types of cognition: “Type I” (implicit, nondeclarative, and automatic) and “Type II” (explicit, declarative, and deliberative). Second, Lizardo et  al. (2016) argue that there are four “analytically distinct domains” of enculturation: “learning,” “remembering,” “thinking,” and “acting” (Lizardo et al. 2016: 289, 291). Third, each domain corresponds to a particular dual-process model that uses a kind of Type I and Type II cognition that is specific to the domain of cultural socialization in which it operates. Each dual-process model therefore has its own corresponding scope conditions and variables. As we discussed in Chap. 1, within the sociology of culture, there are two main models of socialization. Kiley and Vaisey (2020) call these two models the “Active Updating Model” and the “Settled Dispositions Model” (for an extended discussion, see Vaisey and Lizardo 2016; Brett and Miles 2021). Each perspective corresponds to one of the major traditions in the sociology of culture concerning the role of causality. “Active Updating” is part of Culture in Action (e.g., Swidler 2001), and “Settled Dispositions” is a foundational feature of Strong Practice Theory (e.g., Bourdieu 1990). “Settled Dispositions” argues that actors are mainly socialized during childhood. From early formative experiences, then, actors develop the dispositions that they usually rely upon for the rest of their lives. Bourdieu’s habitus is a classic example of this perspective (Bourdieu 1990; for summaries, see Vaisey and Lizardo 2016; Kiley and Vaisey 2020). “Active Updating,” conversely, argues that people’s socialization varies according to the environment. As the environment and social interaction change, so do people’s dispositions and behaviors. Socialization is then a dynamic process that occurs throughout the life course (Joas 1996; Swidler 2001; Gross 2009; Kiley and Vaisey 2020). Subsequent work on dual-process models have then argued that both of these perspectives come into play (Vaisey and Lizardo 2010, 2016; Srivastava and Banaji 2011; Hoffmann 2014; Miles 2015) and more recent work in Strong Practice Theory has also argued that both of these perspectives are useful (Lizardo and Strand 2010; Kiley and Vaisey 2020).

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Recent work in this area focuses on the relationship between socialization and attitudes (Vaisey and Lizardo 2016; Kiley and Vaisey 2020; Brett and Miles 2021; Broćić and Miles 2021) and socialization and political orientation (Edelmann and Vaisey 2021)—which are both beyond the scope of this book. While work on dual-process models of action has attempted to bridge the “Active Updating Model” and the “Settled Dispositions Model” (Vaisey and Lizardo 2010, 2016; Srivastava and Banaji 2011; Hoffmann 2014; Miles 2015), other dual-process models provide the scaffolding to understand both processes of socialization (Vila-Henninger 2015, 2020; Lizardo et al. 2016; Lizardo 2017). Here, it is important to note the emergence in the latter literature of the distinction between Type I and Type II processes of socialization. The debate, then, concerns whether Type I and Type II processes of socialization occur through a model in which these two processes are dissociated and thus mostly independent (Lizardo 2017) or whether these two processes of socialization are part of a model where Type I and Type II processes are also at times in conflict or work together (Vila-Henninger 2015, 2020). In this book, I build on my previous work and outline a model in which Type I and Type II processes are both independent but are also may be in conflict or work together—depending on the context. To do so, I build on work in neuroscience (Cushman 2013; Crockett 2013; Greene 2017; Lockwood et al. 2020). Recent work has also argued that there is a distinction in socialization between internalization of culture through instruction versus through interaction (Guhin et al. 2021; Lizardo 2021). Crucially, my model accounts for social learning via both interaction and instruction.

Conclusion Now that we have reviewed the literature on socialization and models of action, we can proceed to critique both using findings from psychology and neuroscience (Chap. 4). Doing so carries out my theoretical and empirical agenda (Chap. 1) by applying my conceptual framework for theory-building (Chap. 2) to the literature reviewed in this chapter. I will then proceed from the critique to build a dual-process model (Chap. 5) and then test this model empirically (Chap. 6).

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Tetlock, Philip E., Orie V. Kristel, S. Beth Elson, Melanie C. Green, and Jennifer S.  Lerner. 2000. “The Psychology of the Unthinkable: Taboo Trade-Offs, Forbidden Base Rates, and Heretical Counterfactuals.” Journal of Personality and Social Psychology 78(5):853–70. doi: https://doi.org/10.1037/ 0022-­3514.78.5.853. Tversky A, and Kahneman D. 1974. “Judgment under Uncertainty: Heuristics and Biases.” Science (New York, N.Y.) 185(4157):1124–31. Vaisey, Stephen. 2008a. “Reply to Ann Swidler.” Sociforu Sociological Forum 23(3):619–22. Vaisey, Stephen. 2008b. “Socrates, Skinner, and Aristotle: Three Ways of Thinking About Culture in Action.” Sociological Forum 23(3):603–13. Vaisey, Stephen. 2009. “Motivation and Justification: A Dual-Process Model of Culture in Action.” AJS; American Journal of Sociology 114(6):1675–1715. doi: https://doi.org/10.1086/597179. Vaisey, Stephen, and Omar Lizardo. 2010. “Can Cultural Worldviews Influence Network Composition?” Social Forces 88(4):1595–1618. Vaisey, Stephen. 2013. “Is interviewing compatible with the dual-process model of culture?” American Journal of Cultural Sociology 2(1):150–58. Vaisey, Stephen, and Margaret Frye. 2019. “The Old One-Two: Preserving Analytical Dualism in Cognitive Sociology.” Vaisey, Stephen, and Omar Lizardo. 2016. “Cultural Fragmentation or Acquired Dispositions? A New Approach to Accounting for Patterns of Cultural Change.” Socius: Sociological Research for a Dynamic World 2:237802311666972. Vanina Leschziner, and Adam Isaiah Green. 2013. “Thinking about Food and Sex: Deliberate Cognition in the Routine Practices of a Field.” Sociological Theory 31(2):116–44. doi: https://doi.org/10.1177/0735275113489806. Vila-Henninger, Luis Antonio. 2015. “Toward Defining the Causal Role of Consciousness: Using Models of Memory and Moral Judgment from Cognitive Neuroscience to Expand the Sociological Dual-Process Model.” JTSB Journal for the Theory of Social Behaviour 45(2):238–60. Vila-Henninger, Luis Antonio. 2020. “A Theory of Popular Political Legitimation: A Dual-Process Model Approach to Legitimation and Political Socialization.” JTSB Journal for the Theory of Social Behaviour 50(4):490–515. Waytz, Adam, Ravi Iyer, Liane Young, Jonathan Haidt, and Jesse Graham. 2019. “Ideological Differences in the Expanse of the Moral Circle.” Nature Communications 10(1):4389. doi: https://doi.org/10.1038/s41467-01912227-­0. Williams, Lawrence H. 2021. Thinking through dilemmas: schemas, frames, and difficult decisions. New York: Routledge. Winchester, Daniel. 2016. “A Hunger for God: Embodied Metaphor as Cultural Cognition in Action.” Social Forces 95(2).

CHAPTER 4

The Dichotomy and the Data

Introduction What role does Type II (deliberative) cognition play in decision-making? How does it interact with Type I (automatic) processes? These two questions constitute two important gaps in what Omar Lizardo calls “Strong Practice Theory” (Lizardo and Strand 2010) and Gabriel Ignatow calls the “French tradition of psychologically informed sociology” (Ignatow 2019) that extend from Pierre Bourdieu’s habitus to Stephen Vaisey’s sociological dual-process model and beyond. Strong Practice Theory generally argues that cultural ends affect action primarily through subconscious embodied cultural schemas—which are a Type I process. While this addresses the issue of how cultural ends can affect action in the absence of conscious logically coherent frameworks, it does not provide a detailed account of how Type II cognition, as well as its interaction Type I processes, affect moral judgment and decision-making. The goal of this book is to begin to fill these gaps in Strong Practice Theory and the sociological dual-process model literature by providing an empirical account for how and when Type II cognition affects decision-­ making independently, how and when it acts to override Type I processes, and how and when Type I and Type II processes interact to affect moral judgment and decision-making. Echoing Vaisey and Lizardo (2010: 1612), I argue that it is important to continue to expand sociological models of culture’s effects on action by drawing on models from cognitive © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 L. A. Vila-Henninger, Socialization, Moral Judgment, and Action, https://doi.org/10.1007/978-3-030-88278-5_4

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science—and especially by using dual-process models. Given that each dual-process model has a scope within which it applies (Lizardo et al. 2016), I will only use findings from cognitive science that help us to understand moral judgment—which is the scope condition for the sociological dual-process model. I argue that Strong Practice Theory and the subsequent literature have two key limitations: Dichotomy and Data. First, beyond an analytic dualism (Vaisey and Frye 2019), this literature establishes a dichotomy between Type I and Type II processes in which the two are essentially mutually exclusive. I therefore use relevant findings from cognitive science to evaluate the foundations of the sociological dual-process model: Bourdieu’s concept of the “habitus” and Vaisey’s (Vaisey 2009; Vaisey and Lizardo 2010) sociological “dual-process model” of moral judgment. I review this literature and then discuss subsequent work that acknowledges that there is a possibility for interaction between the Type I and Type II processes but does not offer a model of how this interaction takes place (Lizardo 2017). Second, I review the data that this literature uses to measure Type I processes. As work has highlighted (Vila-Henninger 2015; Miles 2019; Miles et al. 2019), the literature has used data for Type I processes that do not solely measure these processes and therefore has issues with construct validity. I then expand my review of this problem and focus on the issues with construct validity for subsequent work in this literature that analyzes “schemas”—which are widely accepted as Type I processes. Thus, we see the two issues emerge as “Dichotomy” and “Data.” For each limitation, I will therefore use cognitive science to critique both Strong Practice Theory literature and the subsequent literature.

Dichotomy While we have seen that dualism in the sociological dual-process model as the analytic distinction between Type I and Type II processes (Vaisey and Frye 2019: esp. 112–3) is useful and has been confirmed empirically by neuroscience (for a summary, see Greene 2017), a false dichotomy has emerged in the sociological dual-process model literature in which Type I and Type II processes cannot interact and are essentially mutually exclusive. I therefore use work from cognitive science to critique this dichotomy. I proceed with the Dichotomy section as follows: First, I outline the claims made by the sociological dual-process model concerning the causal

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role of Type II conscious and Type I subconscious systems. I then summarize models of memory and moral judgment from cognitive neuroscience. My discussion of the memory literature supplements Stephen Turner’s (2012) discussion of the problematic conceptualization of “tacit” knowledge by providing an empirical framework from cognitive neuroscience that can be used to understand tacit and explicit knowledge. Subsequently, I outline the role of “executive functions,” also known as “cognitive control,” in decision-making and then summarize two predominant and competing models of moral judgment from cognitive neuroscience that account for executive functions. I use each model to evaluate the corresponding claims of the sociological dual-process model in order to provide an empirical framework that begins to fill the two aforementioned theoretical gaps. In this process, I create a conceptual roadmap that helps translate concepts from cognitive neuroscience into sociological terms. This discussion builds on Ignatow’s (2007, 2009, 2019) work by providing a framework through which we can understand interactions between the habitus and discursive consciousness. Next, I use findings from the literature in cognitive science of categorization to evaluate the sociological dual-process model and its dichotomy between Type I and Type II processes. I conclude by discussing “dichotomy” in the literature since the sociological dual-process model. Sociological Dual-Process Model Dual-process models are the predominant model in cognitive science for conceptualizing mental systems and expand beyond cognition to include emotion. Jonathan Evans’ (2008) review of the dual-process literature found 14 different dual-process models which spanned 4 clusters of a total of 44 mental processes (Evans 2008: 257). Two important points need to be made at this juncture. First, while a giant body of literature uses the dual-process heuristic, there is no consensus on what a “dual-process model” is. Second, there is mounting evidence that Jonathan Haidt’s (2001, 2005) “dual-process” model, which is foundational for the sociological dual-process model, does not accurately characterize moral decision-making (Forbes and Grafman 2010; Greene et al. 2004; Moll et al. 2005; de Oliveira-Souza et al. 2011; Paxton et al. 2012). While the attempt to reappropriate a dual-process model from cognitive science for sociological use is innovative and important, I argue that the use of one dual-process model leaves much room for expansion by

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incorporating additional models of mental processes. Such expansion is necessary given that Strong Practice Theory and the sociological dual-­ process model do not provide a clear model for the causal role of discursive consciousness in decision-making, how discursive consciousness overrides practical consciousness, or how discursive and practical consciousness interact to affect decision-making. These gaps have their origin in Bourdieu’s habitus. Bourdieu explicitly addresses critiques of the habitus by arguing that consciousness can override dispositions or can regulate them by pitting them against one another (Bourdieu and Wacquant 1992: 136). He then extends this claim by arguing that “agents become something like ‘subjects’ only to the extent that they consciously master the relation they entertain with their dispositions” (Bourdieu and Wacquant 1992: 137). This description complements Bourdieu’s characterization of the habitus and its role in determining action by creating a role for consciousness to regulate unconscious dispositions as well as override them. However, Bourdieu does not theorize how or when either of these functions of consciousness occur in social life. This thread carries over to the work of Stephen Vaisey, who argues that discursive consciousness (Type II) “can, under the right conditions, override the habitus” (Vaisey 2008: 610). Vaisey posits that actors are “primarily driven by deeply internalized schematic processes” (Vaisey 2009: 1687). Here, Vaisey employs Haidt’s metaphor of a rider on an elephant and contends that the “rider,” or discursive consciousness, “can slowly train the elephant [practical consciousness] over time or perhaps trick it into going a different way” (Vaisey 2009: 1683). These two central models for Strong Practice Theory acknowledge that conscious cognition can override subconscious dispositions or impulses, or can directly affect decision-making. However, neither of these models or their subsequent iterations (Vaisey and Lizardo 2010; Vaisey 2013; Ignatow 2019; Vaisey and Frye 2019) have used findings from cognitive science to address when and how these two phenomena occur. The closest sociologists have come to filling these gaps is work that specifies conditions under which it is plausible that discursive overrides practical consciousness (Lizardo and Strand 2010; Martin and Desmond 2010; Abramson 2012; Vila-Henninger 2015; Vaisey and Frye 2019). Furthermore, except for Ignatow (2007, 2009, 2019), this body of literature does not address how these two forms of cognition interact to affect decision-making—thus seeming to imply that Type I and Type II cognition are mutually exclusive.

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Using Models from Cognitive Science In a classic review of the sociology of culture and cognition, Karen Cerulo (2010; for further discussion see Cerulo et al. 2021) argues that “interdisciplinary cross talk” with cognitive science and neuroscience is essential to helping sociologists understand variation in cognition and social action (Cerulo 2010: 128). While important steps have been taken to engage in such cross talk, I argue that there can and should be a continued appropriation of models from cognitive science. In particular, Turner (2007b) and Lizardo (2009) lay a foundation for theory-building by using cognitive science and cognitive neuroscience. This work complements a wide array of theory building that emerged at the beginning of the Culture and Cognition literature that sought to integrate findings from cognitive science into sociological work (DiMaggio 1997; Bergesen 2004a, 2004b; Ignatow 2007, 2009; Lizardo and Strand 2010; Vaisey 2009, 2010; Vaisey and Lizardo 2010) and cognitive neuroscience (Lizardo 2007; Turner 2002, 2007a, 2012; Pitts-­Taylor 2013). While much work uses cognitive science findings to develop sociological theories, the only work that has imported an entire model is the sociological dual-process model (Vaisey 2009; Vaisey and Lizardo 2010). While some doubt has been cast on the methods that this model uses (Pugh 2013; Jerolmack and Kahn 2014a, 2014b; Vila-Henninger 2015; Miles et al. 2019), as well as the theoretical interpretation of the role of discursive consciousness (Pugh 2013; Vaisey 2013; Vila-Henninger 2015, 2020; Lizardo et al. 2016; Miles et al. 2019), to my knowledge sociologists of culture have yet to create an alternative theory that uses an entire model from cognitive science as its basis—except for Luis Vila-Henninger (2015, 2020) and Omar Lizardo (2017). This book’s agenda, then, is to use the strategy of model importation employed by the sociological dual-process model (Vaisey 2008, 2009; Vaisey and Lizardo 2010) in order to expand and refine it in a way that fills the aforementioned theoretical gaps. Specifically, I use models from cognitive neuroscience on memory and moral judgment as resources. In this way, this book builds on Ignatow’s scholarship in an effort to refine and expand habitus (Ignatow 2009).

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Memory Within cognitive neuroscience, there is a relative consensus over the model of memory (for a review of the consensus and the emergence of the model, see Squire 2004; Squire and Wixted 2011). Memory systems can be understood in terms of their temporal characteristics (working/short term versus long term), as well as their functional characteristics (declarative/ explicit versus nondeclarative/implicit), and can be thought of as the mechanisms through which different types of content are encoded in the brain. Memory processes, on the other hand, are cognitive functions that support the activation and use of different memory systems in the performance of specific tasks (for a review of the literature, see Markowitsch 2000; Squire 2004; Salmon and Squire 2009; Squire and Wixted 2011). In terms of temporal characteristics, memory systems have been classified as working memory and long-term memory. Working memory is a form of short-term information storage that involves attention and consciousness and is “under the control of a fronto-parietal network” (Markowitsch 2000: 269). This memory is retained consciously (or “online”) and lasts up to several minutes (Markowitsch 2000: 266). This information can be consciously manipulated, encoded at a surface level, and could be in the process of being prepared for long-term storage (Markowitsch 2000: 263). By definition, this storage system is limited in its capacity and much of the information that it holds is not converted into long-term memory. Long-term memory is the storage of information “off-line,” which can then be retrieved and used after long periods of time and involves deep, often semantic encoding (Markowitsch 2000: 263). Long-term memory is encoded on a deeper level through its incorporation into a neural network, usually in the limbic system (Markowitsch 2000: 269). In order to integrate memories into this neural network, the medial temporal lobe and diencephalic structures are activated. Retaining information as long-term memory often requires continual activation of that information and association with other memories in the network. In terms of functional characteristics, memory systems can be thought of as declarative/explicit or as nondeclarative/implicit (for a review, see Squire 2004; Squire and Wixted 2011). Declarative/explicit memory involves conscious recollection and includes two subsystems of memory. The first is semantic memory, or the knowledge of facts. This knowledge is general and does not require temporal cues. The second is episodic

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memory or “the capacity to re-experience an event in the context in which it originally occurred” (Squire 2004: 174). In other words, information that is temporally bound and is often related to temporal or spatial cues (Markowitsch 2000: 264; Squire 2004: 174; Salmon and Squire 2009: 570). These two subsystems are distinct because semantic memory is more resilient, while episodic memory is more susceptible to impairment. Furthermore, semantic memory is encoded independently of episodic memory, while episodic memory is encoded via semantic memory (Markowitsch 2000: 265; Squire 2004; Squire and Wixted 2011). Nondeclarative or implicit memory is information that is expressed through action rather than conscious recollection. Implicit memory alters action subconsciously and includes procedural memory, priming, conditioning, and nonassociative learning. Procedural memory involves the acquisition of motor skills and “rules and sequences” (Markowitsch 2000: 267) and is processed mainly in the basal ganglia and cerebellum. Priming and perceptual learning involve responses to cues that are associated with given outcomes in previous contexts, while conditioning involves a continual association of an event with an outcome (Markowitsch 2000: 267–8; Squire 2004; Squire and Wixted 2011). Memory processes can be thought of as cognitive functions that support the activation and use of different types of memory systems in the performance of specific tasks. These functions include encoding, retention, and retrieval. Encoding involves the processes through which memories are stored in the brain. This usually occurs in the form of words or images. Retention, which involves storage and maintenance, is the process through which the brain stores information. Finally, retrieval is the process of accessing information. It can involve free recall, which involves ready, explicit access to a memory, or recognition, which merely requires the identification using explicit memory (Markowitsch 2000; Squire 2004; Squire and Wixted, 2011). Declarative and Nondeclarative Memory and the Sociological Dual-Process Model The previous review is useful for establishing the distinctions between different memory systems and processes, as well as when and how memory can play a role in decision-making. A key issue for the sociological dual-­ process model concerns how memory systems store and activate cultural schemas. The sociological dual-process model argues that cultural

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schemas are “largely unconscious networks of neural associations that facilitate perception, interpretation, and action” (Vaisey 2009: 1686). In this model, cultural ends are automatically generated by these schemas, which influence decision-making and are encoded in the form of procedural memory (Lizardo and Strand 2010; Vaisey and Lizardo 2010). In the words of Vaisey and Lizardo (2010: 1612), “‘[s]ense-making’ discourse is the tip of the cultural iceberg; submerged in less-accessible regions is a realm of implicit culture encoded in non-linguistic form, stored in procedural and not declarative memory, with the potential to shape our perceptions and reactions to events.” This characterization is curious, given the limitations of procedural memory. While procedural memory is essential in learning and executing concrete tasks, many other types of nondeclarative memory are essential for schema acquisition and use—such as priming. Furthermore, to argue that declarative memory plays only a marginal role in cultural acquisition and action is inconsistent with findings from cognitive neuroscience. Studies have found that not only are different memory systems employed in different contexts but that both declarative and nondeclarative memory can be used to learn the same task, depending on the actor’s learning strategy. Often, when learning a habit, declarative and non-declarative memory systems compete to control habit acquisition. At first, declarative memory tends to be more active as actors attempt to memorize the task. However, as performance improves, procedural memory is favored (Squire 2004: 174). Similarly, declarative/explicit and nondeclarative/implicit memory can be simultaneously employed. Larry Squire gives the example of a child being traumatized by a dog. The child will retain an episodic memory of the event, and might also develop a fear of dogs that takes the form of an implicit disposition (Squire 2004: 174). All of this is very much in line with accounts that stress the context-­ dependent nature of cognition (Shepherd 2011; Abramson 2012). Rather than claiming that one memory system has primacy over the other, it makes more sense to understand different memory systems as being deployed to deal with different tasks and execute different functions. Psychologists even argue that “multiple memory systems evolved because they serve distinct and functionally incompatible purposes” (Squire 2004: 174). There are situations in which nondeclarative memory is used instead of declarative memory in the process of decision-making, but to assert that

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implicit memory generally has primacy in cultural learning and decision-­ making overlooks the complexity of the human memory system. In line with Bourdieu’s assessment of the causal role of conscious cognition (Bourdieu and Wacquant 1992: 136–7), the memory literature provides a framework through which we can understand actors overcoming the influence of dispositions through deliberation, which requires declarative/explicit memory: “Declarative memory allows remembered material to be compared and contrasted. The stored representations are flexible, accessible to awareness, and can guide performance in a variety of contexts” (Squire and Wixted 2011: 267). Furthermore, any time an actor uses beliefs or memories of events or the outcomes of events to make a decision, (s)he is using declarative memory. Finally, even habit acquisition requires both explicit and implicit memory. Thus, implicit and explicit memory not only work together, but explicit memory is often indispensable in the early stages of habit formation. A recent review of findings from psychological studies concludes that not only are both declarative and nondeclarative memory systems often simultaneously activated in task performance (e.g., Graybiel 2008: 362), but that nondeclarative and declarative memory systems frequently interact during task performance (Graybiel 2008: 364). These findings help to confirm Gabriel Ignatow’s discussion of the interaction between discursive and practical consciousness (Ignatow 2007, 2009). These findings also raise issues concerning embodiment (e.g., Pitts-Taylor 2013) that are beyond the scope of this book but should be addressed in future work. Moral Judgment For proponents of the sociological dual-process model, culture operates “primarily through embodied and durable schemes of perception, appreciation and action” (Vaisey and Lizardo 2010: 1599, italics in original). Furthermore, “culture is not primarily linguistic, not primarily conscious and not primarily discursive. Instead, it is embodied, tacit, largely unconscious of fast and ‘hot’ cognitive-affective complexes that play a key role in everyday decisions” (Vaisey and Lizardo 2010: 1599; also see Lizardo and Strand 2010; Vaisey 2009: 1685–6). The conclusion is that “actors are driven primarily by deeply internalized schematic processes (“the elephant”/practical consciousness/habitus), yet they are also capable of deliberation and justification (“the rider”/discursive consciousness) when required by the demands of social interaction” (Vaisey 2009: 1687).

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However, findings from cognitive neuroscience suggest that this model places too much emphasis on the effects of subconscious systems/Type I on decision-making (see also Leschziner 2019). Furthermore, this characterization leaves open questions of how Type II processes (discursive consciousness) independently affects action, how Type II processes (discursive consciousness) override Type I processes (practical consciousness), as well as how discursive (Type II) and practical consciousness (Type I) interact to affect action. We can begin to address these gaps by looking at “executive” functions of the brain. There is relative consensus over what “executive functions” are and how they influence decision-making. Executive functions correlate primarily with activity in the prefrontal cortex (PFC) and are top-down, consciously controlled processes of behavioral regulation (for a review of the literature, see Chow and Cummings 2007; Cummings and Miller 2007; Gazzaley and D’Esposito 2007; Knight and D’Esposito 2003). Executive functions integrate input from other areas of the brain, such as sensory or internal emotional states, and then organize behavioral responses, often in response to complex environmental and internal demands. Executive functions allow for the willful response to different situations and involve remembering previous experience, creating a plan of action that incorporates relevant goals, enacting the plan, monitoring and regulating action, and judging when to stop or initiate action. This process then results in the fluent, spontaneous, creative generation of behavior that can be performed according to abstract rules or goals. Executive functions also include planning and manipulating working memory in order to pursue a given strategy, as well as the control and allocation of attention to certain tasks or strategies and away from others. Finally, they allow for the suppression of automatic responses, the acquiescence to or suppression of emotional responses, and the use of automatic responses to motivate goal-oriented behavior. In sum, executive functions generate meaningful, willful behavior by regulating a variety of stimuli and activating an array of neural resources. Models of Moral Judgment from Cognitive Neuroscience Now that we have reviewed the primary functions of cognitive control, or executive functions, we can understand competing models of moral judgment from cognitive science—the most developed of which come from neuroscience. I am selecting moral judgment because it allows us to

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empirically assess the sociological dual-process model (Vaisey 2009; Vaisey and Lizardo 2010) due to its scope condition of moral judgment and adoption of a model of moral judgment from cognitive science (Haidt 2001). Defined by cognitive neuroscientists, moral judgments are “evaluative judgments of the appropriateness of one’s behavior within the context of socialized perceptions of right and wrong” (Forbes and Grafman 2010: 304). The synthesis that I undertake relies on this definition of moral judgment. While sociological dual-process model theorists have thoroughly drawn upon the work of one scholar within moral psychology to inform their analysis, Jonathan Haidt (e.g., 2001), I expand my analysis by using two predominant and competing models of moral judgment from cognitive neuroscience that not only empirically assess Haidt’s perspective, but build upon it: Joshua Greene and colleagues’ Dual-Process model and Jorge Moll and colleagues’ Single-Process model. A key difference between Moll’s model and Greene’s model is the role of representation. Moll and colleagues argue that moral judgment relies on the integration of morally relevant representations, while Greene argues it relies on two distinct psychological processes. While this debate is beyond our scope as sociologists, we can use concrete, empirically defined concepts from each model to refine and expand the sociological dual-process model—as I do in Chap. 5. The Dual-Process Model in Cognitive Neuroscience In cognitive neuroscience, Joshua Greene and his colleagues (2001, 2004, 2007, 2012; see also Cushman 2013; Crockett 2013; Greene 2017; Lockwood et al. 2020) develop a dual-process model of moral decision-­ making that provides a “synthetic theory of moral judgment” (Greene et al. 2004: 397). Greene’s model is a synthesis of rational dual-process models (e.g., Kohlberg 1969) that argue that morality is driven by conscious reasoning, and intuitionist models (e.g., Haidt 2001) that argue that moral judgments are driven by subconscious impulses. Greene’s model is based on fMRIs of brain activity for subjects responding to moral dilemmas (Greene et al. 2001, 2004; Greene 2007; 2012), which builds on an important interdisciplinary literature that focuses in particular on the “Trolley Dilemma.” In Greene’s model, there are two major axes along which moral judgment is affected. The first axis is neurological function and the second is

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social context. For the first axis, Greene finds that “[n]egative emotional response…drives moral disapproval” (Greene 2007: 322, for a list of the activated brain areas, see Greene et al. 2004: 390), while when there are no emotional response actors “engage in utilitarian moral reasoning (aggregate cost–benefit analysis), which is likely subserved by the dorsolateral prefrontal cortex (DLPFC)” (Greene 2007: 322; see Greene et  al. 2001 and 2004 for empirical evidence). When a moral circumstance invokes emotional response and utilitarian moral reasoning, “conflict is detected by the anterior cingulate cortex [ACC], which signals the need for cognitive control, to be implemented in this case by the anterior DLPFC [Brodmann’s Areas (BA) 10/46]. Overriding prepotent emotional responses requires additional cognitive control and, thus, we find increased activity in the anterior DLPFC when people make difficult utilitarian moral judgments” (Greene 2007: 322; see Greene et al. 2004 for empirical evidence). A brief discussion of activity in the dorsal lateral prefrontal cortex (DLPFC) helps to make Greene’s model more intuitive. Activity in the DLPFC is often correlated with cognitive control over action (executive function) as well as organizing volitional responses to environmental cues (see, e.g., Latinus et al. 2010). In this sense, responses to moral dilemmas that correspond to activity in the DLPFC could be understood as the DLPFC using its conscious control to make utilitarian judgments. Similarly, Greene’s findings that the anterior DLPFC is active when subjects must override emotional responses to make utilitarian judgments make sense given the correlation found in other studies between activity in the DLPFC and mediation of automatic responses to external stimuli. The DLPFC, then, can be interpreted as a source for conscious/Type II override of automatic emotional responses to moral dilemmas. The second axis concerns the level of personal involvement and characteristics of the moral dilemma in which the subject is involved. Greene and colleagues find that different situations elicit different types of neural responses (Greene et al. 2001, 2004; Greene 2007; Paxton et al. 2012). Their findings suggest that increased personal involvement in a situation increases emotional response, while “difficult” moral situations, meaning moral dilemmas in which “action that would normally be judged immoral…is favored by strong utilitarian considerations” (Greene et  al. 2004: 391), elicits “cognitive control” that uses utilitarian reasoning to override emotional responses (Greene et al. 2004).

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Given the findings of Greene and his colleagues, the sociological dual-­ process model’s characterization of culture in action seems to address only part of moral decision-making. Greene defines emotional responses as evolutionarily developed “domain-specific social-emotional dispositions” (Greene et  al. 2004: 389), thereby implying that they are mostly automatically generated by subconscious systems. In the sociological dual-­ process model, practical consciousness is conceptualized as using subconscious schemas to produce moral intuitions, impulses, and dispositions (e.g., Vaisey 2009; Vaisey and Lizardo 2010). Vaisey characterizes these schemas as “emotionally charged” and argues that they “influence the way a person deploys ‘shallower’ discursive elements” (Vaisey 2013: 4). Given these definitions, it is reasonable to argue that some emotional responses to moral dilemmas are mostly generated by Type I/practical consciousness. However, it is important to note that emotions cannot be reduced to either Type I or Type II processes. Furthermore, although utilitarian reasoning and discursive consciousness have differing definitions, they are both defined as conscious and “deliberate” processes that are capable of reasoning. Using Greene’s model and definition of moral decision-making components (utilitarian reasoning, cognitive override, and emotional response dispositions), the sociological dual-process model can be extended to address how utilitarian reasoning affects moral decision-making, as well as how cognitive control overrides emotional responses to affect moral judgment. Such an extension is critical because the sociological dual-process model does not provide a theoretical account of how utilitarian reasoning or cognitive override affects decision-making. Second, from the perspective of Greene’s dual-process model, the causal role of utilitarian reasoning and emotional response, and by extension discursive and practical consciousness, is socially mediated. This is an important addition to the sociological dual-process model’s accounts of when discursive and practical consciousness affect decision-making. I argue that it is reasonable to interpret Greene’s findings as implying that little or no direct personal involvement increases the probability that actors use utilitarian reasoning with no emotional response to override, while direct personal involvement increases the probability that emotional responses determine moral judgments. Additionally, “difficult” moral decisions increase the probability that actors use cognitive control to override automatic responses in the use of utilitarian reasoning. Finally, Greene’s model suggests that while Srivastava and Banaji (2011) provide an important

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methodological tool for measuring subconscious processes, we cannot rely on the measurement of subconscious processes alone to understand moral judgment. Since these studies, Greene and others in cognitive science (Crockett 2013; Cushman 2013; Greene 2017; Lockwood et al. 2020) have greatly expanded this model. Given the strong evidence for this expanded model, I use it as the core of my dual-process model—which I develop in the next chapter (Chap. 5). Moll and Colleagues’ Single-Process Model An opposing model in cognitive neuroscience, advanced by Jorge Moll and his colleagues, argues that to make moral judgments actors use an interconnected neural network. The most important tool that this network produces for moral decision-making is the “event-feature-emotion-­ complex” (EFEC). The EFEC is a framework through which “moral cognitive phenomena emerge from the integration of content and context-­ dependent representations in cortical-limbic networks” (Moll et al. 2005: 804). The EFEC emerges from real-time interaction between representations of activity in three different neural regions (Moll et al. 2005: 804). This model is based on a decade of fMRI results of neural responses to moral situations, as well as studies of the moral and social dysfunction that results from damage to certain areas of the brain (findings summarized in Moll et al. 2005; Forbes and Grafman 2010; de Oliveira-Souza et al. 2011). First, “action/event sequence knowledge” corresponds with activity in the prefrontal cortex (PFC). The PFC is an area of the brain in which activity is correlated with conscious control and regulation of thoughts and behaviors. In social moral situations, action/event sequence knowledge can be of several types: goals, knowledge of situations and environmental cues, and socially associated emotional knowledge—such as beliefs and attitudes. Different areas of the PFC then use these different types of knowledge to assess, define, and interpret a situation. This cognitive function and its neural substrates employ different types of knowledge and beliefs about the characteristics of a situation and the agent’s relationship to that situation in order to make judgments about how the actor should behave. Moll et al. (2005) argue that this function not only helps an agent to define a situation but also to make predictions about its consequences, it also gives actors the ability to plan and pursue their goals given their interpretation of the context and assessment of the future.

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The second region revolves around the temporal lobes and is involved in the perception of social cues as well as the processing of social characteristics to produce social perceptual knowledge. Depending on the situation, the temporal lobes are involved in conscious and/or subconscious interpretation of cues from others—such as body language and vocal intonation—and their association with particular social attributes of social behavior—such as honorability or stinginess (e.g., Moll et al. 2005: 805). While the processing of these attributes varies according to the situation, the knowledge of what these cues and characteristics mean is semantic, and thereby conscious and linguistically encoded (Moll et al. 2005: 805). This is because knowledge that is independent of context is classified as semantic, which is a type of declarative memory (Squire 2004; Squire and Wixted 2011). Both our interpretation of social cues and our categorization of actions according to their social characteristics are semantic because they are not dependent on one context. If you tell a joke and someone winces, or if you go to dinner with someone and they try to pay less than the full amount they owe, you rely on general knowledge of social characteristics to interpret what the other person is doing and subsequently categorize their action. This is not to say that humans are born with the concept of “stinginess.” Instead, it means that through social interaction humans learn and develop a general knowledge that they can use to interpret and classify actions and actors across situations. This is very much in line with Sewell’s (1992) synthesis of the work of Giddens and Bourdieu, who argues that conceptual frameworks are transposable across situations, but that outcomes have degrees of unpredictability because situations are not homogenous. Furthermore, these findings reaffirm Bourdieu’s (1984, 1990) description of the habitus as consisting of transposable dispositions. However, from Moll’s single-­ process model, we find that more than just subconscious, embodied dispositions are transposed across situations. Instead, agents use transposable systems of conscious knowledge in their conscious and/or unconscious interpretation of a social situation en route to making a moral judgment about an element of that situation. This reaffirms Sewell’s (1992) description of social structures as “mutually sustaining schemas and resources that empower and constrain social action” (Sewell 1992: 19). The third region corresponds to motivations. Moll and his colleagues identify a variety of subcortical neural areas that are involved in the generation of basic emotional and instinctive drives. The corresponding function is defined as “central motivating states.” Basic emotional states are

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generated by subcortical limbic areas of the brain (discussed further in Moll et al. 2005; Forbes and Grafman 2010). These states are then combined with semantic knowledge that applies to the situation (event/action sequence knowledge) and social and environmental cues gathered in the situation (social perceptual knowledge) to create context-dependent intuitions. This process of interaction provides the emotional motivation necessary to carry out a goal, the intuition to respond to a given social situation, or the impulse of when and how to restrain a basic motivating emotion, such as anger. This third component has much to contribute to the sociological dual-­ process model’s definition of “motivation.” The sociological dual-process model argues that “there is a robust notion of motivation implicit in the schema concept itself, since schemas automatically generate different evaluative and behavioral responses according to the interaction of the neural connections and the nature of the inputs” (Vaisey 2009: 1687). In this model, motivation is generated by subconscious schemas and is not consciously accessible. Using Moll’s model, we can conceptualize motive states as being combined with an actor’s social knowledge and perception of situational cues to generate motives through the interaction of conscious and subconscious systems. In these terms, it is not accurate to claim that fully formed motives are generated by Type I subconscious cultural schema. Instead, motive states are subconsciously generated and are then integrated with event/action sequence knowledge and social perceptual knowledge to create motivations, which then drive action. These motivations would then be available to varying degrees to an actor’s consciousness. In essence, this is the marriage of Weber’s (1978 [1922]) description of meaning-making with Bourdieu’s habitus. Automatic responses, beliefs, and more general knowledge are all utilized to create meaning, interpret situations, generate motives, and determine actions. It is not an issue of whether habits or practical schemas have superiority. Instead, activities in different areas of the brain interact and use resources available to them to interpret and define a situation. This process, which draws upon conscious and unconscious resources, is itself a conscious process in which the agent actively interprets and assesses a situation, makes judgments about potential outcomes of the situation, and then decides on the most appropriate action to pursue given his/her assessment of the situation. Thus, while habits and dispositions are important, they are not the sole or even the driving neural function in moral decision-making. Instead, they are one

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set of resources among many that are used to define a situation and help agents make decisions about how to behave and pursue their goals. One important note is that Moll’s single-process model is based on the hypothesis that there is a temporal binding of cortical and subcortical activity to produce moral judgments. In other words, the brain can combine inputs and representations generated by different neural functions in real time through a process called “temporal binding,” which then leads to given moral judgment. While the technology is still being developed to measure whether or not temporal binding takes place for moral judgment, this process has already been established in areas such as visual cognition, where the brain combines input from different visual systems in real time to create what we experience as vision (e.g., Moll et al. 2005) This model can be used in several important ways to further refine and expand the sociological dual-process model. First, it builds on findings that strongly suggest that reason and emotion are strongly connected and that agents cannot effectively reason without having functioning neural capacities for emotion (Damasio 1994). This means that damage to one aspect of the network affects overall moral judgment (de Oliveira-Souza et al. 2011). Another important contribution is the empirical framework for understanding a variety of schemas active in moral judgment, conceptualized by the single-process model as the EFEC, as well as how these schemas are integrated and utilized to affect moral decision-making. The single-process model’s nuanced definition of motivation, its distinction between “motivation,” “motive states,” and “intuitions,” and its account of the causal role of these three functions are additional contributions. An expansion of the sociological dual-process model based on the single-­process model would argue that agents use a variety of knowledge that informs them about social characteristics, body language, and environmental cues and event sequences (Moll et al. 2005) to make sense of a situation and decide how to behave. In other words, humans are motivated by a variety of factors that often intersect, and subsequently impact their orientation and interpretation of the world, in turn affecting how they make judgments and act in a given situation. In this model, almost all moral decisions are made through an interaction between conscious and subconscious processes, which are then represented in the EFEC and used for decision-making. This model not only shifts the emphasis of the causal role of cultural ends in moral decision-making to an interaction between conscious and subconscious processes, but specifies a concrete, empirically supported set

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of mechanisms for this process. In this way, it fills an important gap in Strong Practice Theory as well as shifts the causal primacy from subconscious schemas to a more complex interaction between conscious and subconscious processes. Furthermore, this perspective of the role of conscious/ subconscious interaction in decision-making reaffirms the conclusion made by Baumeister et al. (2011) after their review of over 100 psychological studies, who find it plausible that almost every human behavior is the result of interaction between conscious and subconscious processes (Baumeister et al. 2011: 331). Expanding the Habitus and the Sociological Dual-Process Model Using Neuroscience A sociological dual-process model that is refined and expanded using the aforementioned models from cognitive neuroscience from this chapter can not only provide accounts of how Type II processes affect moral decision-­ making independently, override Type I processes, and interact with Type I processes, but should also adjust its conceptions of “practical” and “discursive” consciousness (Vaisey 2009). Instead of a “practical” consciousness (Vaisey 2009), we have seen that there are a variety of automatic mechanisms that are responsible for using cultural ends to affect decision-making. First, procedural memory, along with priming, conditioning, and nonassociative learning, helps to encode habits and subconscious schema. From nondeclarative memory “arise the dispositions, habits, and preferences that are inaccessible to conscious recollection but that nevertheless are shaped by past events, influence our behavior and mental life, and are an important part of who we are” (Squire and Wixted 2011: 267). However, declarative memory is essential in the formation of habits and plays its own crucial role by storing general knowledge as well as knowledge of previous events. In declarative memory, we store event/action sequence knowledge and social perceptual knowledge. We then use perceptions of automatically generated motive states in conjunction with these two forms of knowledge to generate motives, assess moral situations, and make moral judgments. In specific moral dilemmas, we are often driven by emotions or utilitarian judgments. In “difficult” moral dilemmas, in which the greatest benefits are achieved by breaking a social norm, we use Type II executive control to override our Type I reactions and use Type II utilitarian

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reasoning. In this sense, Type II consciousness is not only “discursive” but active and fundamental to the encoding and pursuit of cultural ends. Furthermore, in the formation of habits, declarative/explicit and nondeclarative/implicit forms of memory compete—with declarative memory overriding nondeclarative memory in the beginning stages. In moral dilemmas in which we have little to no personal involvement, Type II utilitarian reasoning can operate without interference from emotions, while in situations in which we are personally involved, Type I automatic responses drive our decision-making. Type II utilitarian reasoning and Type I automatic emotional responses compete during “difficult” moral dilemmas via Type II deliberation (for a developed description, see Chap. 5), with Type II utilitarian reasoning tending to override automatic Type I emotional responses. In general, however, action/event sequence knowledge, social perceptual knowledge, and motive states are hypothesized to interact in the process of moral deliberation and decision-making. This interaction uses action/event sequence knowledge and social perceptual knowledge, which are each formed by the integration of conscious and subconscious functions, to perform a mostly conscious evaluation of moral social situations. The integration of subconsciously generated motive states with action/ event sequence knowledge and social perceptual knowledge produces an EFEC, which is used to interpret a moral situation, create motives, and then generate a response. The EFEC often generates moral intuitions, which can help the actor to consciously determine how to behave. Given this expansion, it seems that the apt metaphor is not a rider on top of an elephant, but a driver in a car. The car, or subconscious/Type I processes, is socially influenced and allows the driver, or conscious/Type II processes, the possibility of switching to “cruise control.” However, cruise control is never enough on its own, as the driver is responsible for deciding when and at what speed to activate or deactivate cruise control. The car is also able to indicate issues that the driver was not aware of— such as low gas or engine problems. The driver can follow these indicators, or impulses, or ignore them at his/her own risk—which is often mediated by the social situation. The driver is required to make important decisions, such as where the car is going, when to go, and how fast. These decisions are based on the driver’s interpretation of the context and the signals given to him/her by the car. The car determines to a large extent what the driver can do, and is responsible for a variety of crucial actions that are beyond the driver’s

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control. However, the car is also responsive to the driver, who can inhibit or manipulate these actions, and allows him/her to accomplish goals that are feasible given the limits and capacities of the car and driver. In the next chapter (Chap. 5), I build on these insights to develop a sociological dual-process model of moral judgment that helps us to understand socialization and social outcomes. I do so by integrating more recent work by Joshua Greene and colleagues (Crockett 2013; Cushman 2013; Greene 2017; Lockwood et al. 2020) that provides a dual-process model of moral judgment based in neuroscience that expands on the earlier work of Greene on dual-process models of moral judgment (e.g., Greene et al. 2001, 2004). The Sociological Dual-Process Model and Categorization The sociological dual-process model (Vaisey 2009; Vaisey and Lizardo 2010) adds three major contributions: (1) a clear role for Type II conscious cognition, that is, that it is essentially disconnected from Type I subconscious processes and largely causally inefficacious, (2) a neurological and cognitive description of how Type I “embodied consciousness” operates, and (3) a description of what is stored and operates as a cultural schema. Categorization is a major feature of this theory. In this section, I briefly outline the sociological dual-process model as it applies to category acquisition and generation, and then use findings from cognitive science to evaluate the sociological dual-process model’s claims. The premise of the sociological dual-process model is that there is an innate “dual-process model of cultural cognition: actors are driven primarily by deeply internalized schematic processes…yet they are also capable of deliberation and justification…when required by the demands of social interaction” (Vaisey 2009: 1687). It is important to recognize, however, that this perspective implies that Type II conscious processes are largely separate from Type I subconscious processes and that they play a minimal causal role in behavior or category generation (Vaisey 2009: 1683). The significance is that Type II consciousness has a clearly defined role, but that Type I subconscious, socially determined cultural schemas are still the center of analytical attention. From this description, it seems as if the sociological dual-process model is arguing that the categories that actors learn through socialization that are accessible to Type II conscious thought are largely causally inefficacious.

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Second, this refurbishment of habitus posits that “culture is not primarily linguistic, not primarily conscious and not primarily discursive. Instead, it is embodied, tacit, largely unconscious and composed of fast and ‘hot’ cognitive-affective complexes” (Vaisey and Lizardo 2010: 1599). This model, then, “enables an investigation of how individuals come to acquire durable dispositions, and how those dispositions go on to shape their objective structural environments…processes through which people shape their relational micro-environment” (ibid.: 1601). The result is that “cultural worldviews…[are] implicit schemes of perception” (ibid.). Subsequently, conscious cultural processes are of little consequence. Instead, “implicit culture encoded in non-linguistic form, stored in procedural and not declarative memory” (ibid.: 1612) takes a predominant role. As it applies to the mechanisms for category acquisition and generation, “what is transmitted is implicit and lives in ‘practical’ and not ‘discursive’ consciousness, the process of cultural transmission of practical culture is itself implicit and diffuse…The most important outcomes of the socialization process are never explicitly transmitted by so-called socializing agents” (Lizardo and Strand 2010: 212). Classification is then learned entirely through socialization and “implies the acquisition of irreducibly embodied schemes of action, stored in procedural memory and manifested as a form of ‘skill’” (ibid.: 211–12). This discussion is interesting because it specifies culture as mostly operating through a specific type of memory, “procedural memory,” instead of declarative memory. Simply defined, “[d]eclarative knowledge referred to knowledge available as conscious recollections about facts and events. Procedural knowledge referred primarily to skill-based information, where what has been learned is embedded in acquired procedures” (Squire and Wixted 2011: 266). The implication, then, is that the majority of culture is acquired and generated through Type I practical action. This proposition has two major implications for innate capabilities for category acquisition. First, humans have an innate capacity to learn categorization through Type I practical social action. Second, categorization schemas are non-­ linguistic/nondeclarative and are thus transposed across contexts in the form of Type I automatic, subconsciously driven physical responses. Consciousness and Category Acquisition Behavioral research has shown that learning involves an interaction between attention, memory, and perception. While these abilities are

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available to a very limited extent to fetuses, all three of these systems generally develop in the first several years of a child’s life and are involved in categorization across all contexts (Needham and Woodward 2009: xviii; Oakes et al. 2009: 151). Neurological findings supplement this account and describe the particular cognitive tasks that are involved in the use of attention, memory, and perception in the process of categorization. In terms of memory, categorization relies on “semantic knowledge,” “spatial working memory,” and “intentional retrieval of verbal and/or nonverbal knowledge” (Nelson and Snyder 2005: 15). Category formation in particular involves conscious judgment and memory (ibid.: 14; Grossman et al. 2002). So, while some aspects of culture do not seem to be encoded linguistically, important elements of it are. Indeed, after reviewing a variety of behavioral studies of infants, Gentner (2005) concludes that “relational information…can be encoded in dozens of different ways, and children have to learn the ways that work in their physical, cultural and linguistic environment” (ibid.: 270). Along with declarative semantic knowledge, spatial working memory, and conscious retrieval of discursive and non-discursive knowledge, categorization involves attention through its exclusion of irrelevant information and its recruitment of perceptually mediated information. The brain then uses this information in concert with previous information, usually encoded semantically, in order to decide how to categorize a novel object (Nelson and Snyder 2005: 15). Furthermore, the ability to categorize develops innately as individuals develop their “information-processing skills…and associative learning” (Johnson 2005: 54; Gentner 2005) An interesting and informative difference that emerges between infant categorization and adult categorization is that for adults, categorization depends on an individual’s “goal, the tasks, and the kinds of similarities that the goals, task, and our knowledge make salient” (Oakes et al. 2009: 147). Categorization is then an active process that is driven by individual experience and cognitive capabilities. Infants, however, do not have access to “an explicit goal of categorizing in familiarization contexts” (ibid.: 152). The result is that infants behave “much like amnesiac patients who do not have the explicit goal of categorization” (ibid.) and categorize in a way that is much more dependent on implicit processes and similarities which are observed in objects (ibid.). One of the earliest innate capabilities, then, seems to be the ability to categorize based on perceived similarities (ibid.: 160), whether in language, visual cognition, or speech (e.g., Younger 1985; Saffran et  al. 1996; Gomez and Gerken 1999; Kirkham

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et  al. 2002: 5). Given the emphasis on perception, categorization by infants is heavily influenced by context (Oakes et al. 2009: 164). Similarly, others have found that changes in infant cognitive ability results in a shift in the process through which infants categorize cues linguistically. Whereas 18-month-olds “readily map all symbol types tested to objects, including gestures, sounds and pictograms” (Namy 2009: 254; also see Namy et al. 2004), by 26 months of age children are more selective in their coding and do not map “arbitrary gestures to object, although they readily map words” (Namy 2009: 254). The conclusion is that by 26 months, children have encoded a variety of symbols linguistically and use their linguistic knowledge to select which cues are relevant for categorization and attention (ibid.: 254, 259). The result is that while “children may begin to use and interpret symbols without understanding their inherently intentional and representational nature…children become increasingly more aware of the ways in which the communicative conventions that govern symbol use and communicative intentions relate to communicative behavior” (ibid.: 260). Furthermore, a similar study found that “young children are able to demonstrate evidence of implicit memory-monitoring skills before the age at which they can verbalize about their knowledge” (Balcomb and Gerken 2008: 758). This, along with a variety of related studies (for a summary, see Balcomb and Gerken 2008), demonstrates that “knowing and being able to make use of the contents of one’s mind represents a continuum of task-particular abilities” (Balcomb and Gerken 2008: 758). A related set of findings adds to this account by demonstrating that while at 9 months infants can classify actors according to their goals, but do not linguistically code this information, by the time they are 13 months old this information is encoded and processed linguistically (Buresh and Woodward 2007: 309). Moreover, the work of Waxman and Booth (2000: B42; 2001) suggests that category acquisition and development is fundamentally semantic and is driven by word learning. All of these findings suggest that while children begin their process of categorization without language and in a way that is driven primarily by implicit association between perceptual commonalities, as they develop they rely on this implicit process less and less—becoming more intentional and goal-oriented in their categorization, more aware of others’ uses of language and categories as intentional, and encode these categories linguistically. Procedural memory, or memory that is subconscious and task-­ oriented, seems to be the primary mechanism for category acquisition for

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children of 18  months, as well as amnesiacs. However, by 26  months, children have begun to move beyond this context-driven mode of classification to one that involves conscious processes and attention to not only one’s own goals but the goals of others. This is echoed in a variety of research on adult categorization, which finds that although “an object is imbued with physical properties…the features of the object that are perceived, attended to, and ultimately encoded are dictated by the observer’s category goals” (Tanaka 2004: 886). The process of categorization is ultimately determined by executive, conscious processes which are localized in “category-tuned neurons” in the prefrontal cortex (ibid.: 885). From the literature on categorization, then, we see the following theme emerge: Type II conscious and Type I subconscious processes, as well as procedural and declarative memory, all play key roles in category acquisition and generation. Furthermore, category acquisition involves a variety of innate neurological processes that span the conscious-subconscious (or discursive-­ practical consciousness) divide as well as the nondeclarative-declarative memory divide. Moreover, in the course of normal neurological development, executive (or discursive) consciousness plays an increasingly central role in the acquisition and use of categories in a way that plays an increasingly important causal role in determining the cultural, and corresponding social, outcome. This is supported by a variety of studies (see above review in this section) that find that after approximately two  years of age, language plays a central role in category acquisition. Categories are increasingly acquired and encoded linguistically and after the early stages of infancy, category acquisition is driven by the agent’s goals as well as the agent’s perception of the goals of others. As a consequence of this, the role that procedural memory—and nondeclarative memory more broadly— plays in category acquisition dramatically decreases after infancy. After reviewing the evidence, I find that for category acquisition and generation, Type I/subconscious/nondeclarative and Type II/conscious/declarative processes can both play a dominant role, or can interact, depending on the situation. Similarly, Type II/conscious/declarative and Type I/subconscious/nondeclarative processes play a causal role by themselves, and also sometimes play a causal role in category acquisition and generation through their interaction. Furthermore, depending on the type of category, procedural and/or declarative memory plays an important role in the acquisition, storage, transposition, and generation of categorization schemas. Finally, humans are not simply guided to acquire

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non-linguistic/nondeclarative categories, but acquire, store, and use categorization systems through a variety of memory systems. The rules of this process are driven by innate functions, but these processes are in no way deterministic. Instead, they provide a framework through which humans can meaningfully confront and respond to variation in social circumstances. These findings then strongly undermine the sociological dualprocess model’s implied dichotomy between Type I and Type II processes and highlight the importance of Type II processes in cultural socialization. “Dichotomy” in Dual-Process Models in Recent Literature Work in the years following Vaisey’s (Vaisey 2009; Vaisey and Lizardo 2010) dual-process model—both from critics and from those in Strong Practice Theory (Vila-Henninger 2015; Lizardo et al. 2016; Winchester 2016; Lizardo 2017; Cerulo 2018; Leschziner and Brett 2019; Leschziner 2019; Miles 2019; Vaisey and Frye 2019; Mohr et al. 2020)—emphasizes or acknowledges the interaction between Type I and Type II processes. Furthermore, as we have seen from the above review of Greene’s work (e.g., Greene et al. 2004), the analytic dualism between Type I and Type II processes is supported by findings from psychology and neuroscience— however, a dichotomy between these two processes is not. The issue, then, is to develop a model in which the interaction of Type I and Type II processes takes place. This has been done in work on creativity and other processes (Winchester 2016; Cerulo 2018; Leschziner and Brett 2019) but has yet to be theorized for sociological dual-process models of moral judgment (except for Vila-Henninger 2020). Thus, in subsequent work, more than an implied dichotomy, we see a gap in models of culture regarding this interaction of Type I and Type II processes. The most relevant and high-profile example in the sociological dual-­ process model literature following Stephen Vaisey’s work (Vaisey 2009; Vaisey and Lizardo 2010) is the model of culture developed by Omar Lizardo (2017). Lizardo applies insights from psychology on memory— namely the distinction between declarative and nondeclarative memory— to make a typology of declarative and nondeclarative culture, as well as to establish a dual-process model in which declarative and nondeclarative processes are dissociable. Lizardo (2017) critiques earlier dual-process models in sociology, arguing “that rather than being the result of a tug of war between cognitive and emotive systems, weak coupling (dissociation) between declarative and nondeclarative commitments at the personal level

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emerges as a natural outcome of the dual enculturation pathways” (Lizardo 2017: 97). While Lizardo (2017) does not explicitly claim that there is a dichotomy between declarative and nondeclarative memory, there is a gap in this theory concerning the processes through which Type I and Type II (or nondeclarative and declarative) processes interact. Rather than interaction, Lizardo speaks of “coupling” and degrees of “dissociation.” For Lizardo (2017: 100), then, the acquisition of declarative and nondeclarative culture varies according to “the environment.” Lizardo’s theory of culture argues that “the two main forms in which personal culture presents itself to the analyst at the personal level—culture as declarative know-that and culture as nondeclarative know-how—are partially (and in many cases completely) dissociable” (Lizardo 2017: 99). Nondeclarative culture can at times have an “indirect effect” on declarative culture (ibid.: 105). However, the gaps here are that there is no clear explanation in this theory of how nondeclarative and declarative culture are dissociable, when they are partially or fully dissociable, or how they interact. Furthermore, Lizardo’s (2017) typology of culture argues that different cultural elements are “declarative” or “nondeclarative” while overlooking cases in which a cultural element can be both declarative and nondeclarative. This typology then seems to imply a dichotomy in which a given cultural element is necessarily either declarative or nondeclarative. If this typology is indeed claiming a dichotomy between declarative and nondeclarative culture, this claim is strongly undermined by findings in sociology and cognitive science. Take “values,” for example. Lizardo (2017: 94) argues that values are declarative, yet sociological research demonstrates the importance of nondeclarative values (Miles 2015). Furthermore, work in cognitive science convincingly shows declarative and nondeclarative memory are often simultaneously activated during task performance (e.g., Graybiel 2008: 362), and that declarative and nondeclarative memory systems interact frequently while performing some tasks (Graybiel 2008: 364). Thus, we see a gap in the more recent sociological dual-process model literature (e.g., Lizardo 2017) concerning how Type I and Type II processes interact, as well as theorization that may imply that there is a dichotomy between declarative and nondeclarative culture.

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Data Second, many contributions to the sociological dual-process model literature use data that do not actually measure the Type I processes the authors claim to be measuring (e.g., Vaisey 2009; Vaisey and Lizardo 2010; Hunzaker and Valentino 2019) or use data that by themselves do not support the author’s claims about measuring automatic processes (e.g., Goldberg 2011; Taylor and Stoltz 2020). I refer to this limitation as “Data.” I begin by discussing the implications of the findings discussed in the “Dichotomy” section on sociological methods that attempt to measure Type I processes—especially as they apply to the sociological dual-process model. I then conclude by using findings from cognitive science to evaluate work on automatic processes—and schemas in particular—in the years following Vaisey’s (Vaisey 2009; Vaisey and Lizardo 2010) dual-­ process model. Implications for Methods That Measure Type I Processes The implications of the research from cognitive science I reviewed in Part 1 (“Dichotomy”) of this chapter pertain to a theoretical debate that underlies the use of sociological methods being addressed in two simultaneous exchanges. First, Allison Pugh (2013) and Vaisey (2013) address the extent to which interview data can be used to understand motives and provide a causal explanation for action. The second exchange was sparked by Jerolmack and Kahn’s (2014a, 2014b) argument that self-report data in general are a poor source of information for understanding action. Several scholars have directly addressed this argument and make compelling arguments for methodological pluralism. At the heart of both the Pugh/Vaisey and Jerolmack and Kahn debates is, as Michèle Lamont and Ann Swidler (2014) point out, a theoretical debate over the nature of the data generated by a given method. While sociological arguments concerning certain methodological limitations are beyond the scope of this book, my discussion does pertain to the underlying theoretical debate about the type of data produced by interviews and self-report surveys. This book also sheds light on an important contribution to these two methods debates that has been overlooked: the use of the Implicit Association Test (IAT) (Shepherd 2011; Srivastava and Banaji 2011). Work on the use of the IAT in sociology has since greatly contributed to the debate (Miles et al. 2019).

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First, self-report forced-choice survey data has long been established in psychology as measuring responses from declarative memory while other techniques are used to measure responses from nondeclarative memory (Greenwald et al. 2009: 19). While this nuance has not been addressed by sociological dual-process model advocates or in either of the aforementioned methodological debates, it has been recognized within sociology (Shepherd 2011; Srivastava and Banaji 2011; Vila-Henninger 2015; Miles 2019; Miles et al. 2019). This distinction has been investigated in psychological research by Greenwald et al. (2009), who compare findings from over 120 different attitudinal studies. Their analysis finds that measures of subconscious attitudes using specialized techniques, such as the IAT, are better predictors of behavior in racial situations where social norms provide an incentive for respondents to misrepresent their beliefs. Furthermore, the IAT has been successfully used in sociological research to measure the effects of implicit attitudes on behavior by Srivastava and Banaji (2011), who demonstrate that IAT is much more accurate at recording respondents’ attitudes in situations where it is normatively advantageous to distort self-report responses. This is because IAT captures implicit attitudes, while self-report forced-choice surveys capture responses from declarative memory. Jerolmack and Kahn (2014b) raise an important point concerning the context-dependent nature of the reliability of self-report surveys. However, this concern has been empirically addressed by Greenwald et al.’s (2009) meta-analysis of the predictive reliability of IAT and self-report surveys. This analysis provides a preliminary framework for understanding which contexts make IAT more reliable than self-report forced-choice survey data. In their meta-analysis, they find that racial and intergroup attitudes are better predictors of action when measured implicitly, while attitudes concerning gender/sexual orientation, consumer preferences, political preferences, personality traits, alcohol and drug use, psychological problems, and close relationships are better predictors of behavior or judgment when measured using self-report forced-choice survey data (Greenwald et al. 2009: 24). While more research can and should be done on contextual variation in reliability, it is important to note that this type of research can be empirically conducted (e.g. Miles et al. 2019). More importantly, Greenwald et  al. (2009) suggest that IAT and self-report forced-choice survey data can be used to complement each other, as the predictive power of attitudinal measures was greatest when IAT and self-report findings were highly correlated.

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As for the theoretical debate concerning self-report forced-choice surveys versus interviews, two important points need to be made. First, findings on the data generated by forced-choice self-report surveys suggest that the thorough and important research done by sociological dual-­ process model proponents that claims to show that cultural ends generated by practical consciousness affect behavior (Vaisey 2009, 2010; Vaisey and Lizardo 2010) actually measures declarative systems and information encoded in declarative memory—or at most, an interaction of automatic and deliberative processes (Miles et al. 2019; Miles 2019). Second, Vaisey contends that interviewers can use discourse to access “implicit cultural content” (Vaisey 2013: 5). If self-report attitudinal data does happen to measure cultural elements that are at least to some degree stored in nondeclarative memory, then it is not directly measuring those elements, but instead measuring how they are perceived by conscious systems and encoded in declarative memory. If a respondent is recalling an event in which an impulse affected his/her decision-making, then (s)he is recounting an episodic memory, which is a form of declarative memory. In this sense, surveys measure conscious recollections of decision-making processes, just as interviews do. The substantive theoretical point is that the primary difference in the mental systems employed by interviews versus surveys is not “discursive” versus “practical” consciousness, but the retrieval of declarative memory through free-recall (interviews) versus recognition (surveys). Although Vaisey (2013) has rescinded part of his claim that interview methods do not substantively capture causal processes, the implication is that they can be used to measure implicit schemas. It is important to note that while dispositions and schema may be nondeclarative, attempting to measure them with forced-choice self-report survey data on beliefs elicits declarative memory (see also Miles 2019). Furthermore, asking a survey respondent about a time that an emotion or impulse affected his/her behavior requires the respondent to recall an episodic memory, which is then reported through the recognition of an available survey response. Thus, while Vaisey claimed that the sociological dual-process model “solves” the problem of how cultural ends can affect decision-making by locating these ends and their coherence in practical consciousness, research using self-report attitudinal data actually demonstrates that the puzzle can be solved by returning, in some contexts, to logical coherence in declarative memory. These conclusions serve to reaffirm Vaisey’s (2013) argument that collaboration is needed between researchers using survey and

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interview methods. Furthermore, these findings should encourage collaboration between researchers using certain types of forced-choice selfreport data based on findings and practices from cognitive science and those using psychological measures of automatic processes. Construct Validity Since Vaisey (2009) This book is responding to foundational work in sociology on dual-­process models in which scholars use self-report survey data that measure Type II cognition to make claims about Type I processes (Vaisey 2009; Vaisey and Lizardo 2010; Hoffmann 2014). Unfortunately, since this influential work, subsequent scholarship shares similar issues with construct validity. A crucial note here is that given the important contributions of cognitive science to understanding cognition empirically, it is imperative that we avoid using philosophical terms in the Sociology of Culture and Cognition for empirical concepts that already exist in cognitive science. An example of this comes from Lizardo (2021a), who advocates, for example, for the use of the philosophical concept of “knowledge-what” while not recognizing that this idea is redundant given the concept of semantic memory from cognitive science (e.g. Markowitsch 2000; Squire 2004; Salmon and Squire 2009; APA 2021). Furthermore, sematic memory is a type of declarative memory, which is a term that has been applied in the Sociology of Culture and Cognition to refer to a form of personal culture, or “declarative culture” (Lizardo 2017). Thus, “knowledge-what” is a form of declarative culture rather than a novel type of personal culture. We see a similar redundance with work using philosophical terms to discuss habit (Lizardo 2021b) and embodiment (Lembo and Martin 2021) that does not address the existence of analogous empirical concepts in cognitive science. The use of these redundant philosophical terms risks causing confusion and could lead to the misinterpretation of results. Returning to the “Data” critique, and building on recent work (Boutyline and Soter 2021; Leschziner and Brett 2021), I argue that the major offender here occurs for the concept of “schemas.” In the foundational work on the sociological dual-process model, cultural schemas are “largely unconscious networks of neural associations that facilitate perception, interpretation, and action” (Vaisey 2009: 1686). Culture then operates “primarily through embodied and durable schemes of perception, appreciation and action” (Vaisey and Lizardo 2010: 1599, italics in original).

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Wood et al. (2018: 246) elaborate that “schemas are a form of nondeclarative memory (Squire 1992, 2004)—acquired, used, and altered through a repeated, automatic process of schematization from experience (Lizardo 2017; Lizardo et al. 2016).” Amir Goldberg even likens schemas to habitus (Goldberg 2011: 1410) and claims that “schemas are not clear sets of behavioral rules but rather implicit recognition procedures that emerge from intricate associational links among salient aspects of our cognitively represented experiences (D’Andrade 1995)” (Goldberg 2011: 1401). The key, then, is that schemas are nondeclarative: they are embodied, automatic, and/or implicit (see especially Boutyline and Soter 2021; Leschziner and Brett 2021). Stephen Vaisey (Vaisey 2009) established the use of forced-choice self-­ report data on moral beliefs as a methodological practice for measuring schemas in the sociology of culture. This practice was then used in subsequent work (Vaisey and Lizardo 2010; Hoffmann 2014). Vaisey, however, used one item from a forced-choice self-report survey question as evidence of a schema. Subsequent work demonstrates that forced-choice self-report survey data on beliefs and attitudes cannot be used to measure automatic processes—such as schemas (Vila-Henninger 2015; Miles et al. 2019; Miles 2019). However, scholars have developed this practice by claiming to measure schemas among forced-choice self-report survey data using statistical techniques (Goldberg 2011; Boutyline 2017; Hunzaker and Valentino 2019; Taylor and Stoltz 2020)—an approach that is advocated by some leading scholars in the sociology of culture (Mohr et al. 2020: 44–7). Researchers have also extended this practice to interview data (Pugh 2013; Ecklund et al. 2017; Frye 2017; Rotolo 2020, 2021) and ethnographic data (Leeds 2020). The issue is that forced-choice self-report survey data on beliefs and attitudes, as well as semi-structured interview data, elicit respondents’ declarative memory (Squire 2004; Greenwald et  al. 2009; Squire and Wixted 2011). Recall that “[d]eclarative memory allows remembered material to be compared and contrasted. The stored representations are flexible, accessible to awareness, and can guide performance in a variety of contexts” (Squire and Wixted 2011: 267).” This means that discourse, attitudes, or any representation of which the respondent is aware is declarative memory and is at most processed by both Type I and Type II systems (Graybiel 2008; Miles 2019).

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Here, we need to note that scholars have developed tools to measure automatic, implicit, or nondeclarative cultural elements—such as values (Miles 2015) and beliefs (Shepherd and Marshall 2018). The key is that if schemas are nondeclarative, they need to be measured with techniques that elicit nondeclarative memory from respondents. Building on work in anthropology (e.g., D’Andrade 1995), scholars argue that associations in interviews (Mohr et al. 2020: 44) or statistical associations within self-report survey data that are not explicitly identified by respondents themselves are examples of schemas (Goldberg 2011; Boutyline 2017; Hunzaker and Valentino  al. 2019; Taylor and Stoltz 2020). However, this neglects a key nuance in declarative memory. Recall that retrieval in declarative memory operates through “free recall” and “recognition” (Markowitsch 2000; Squire 2004; Squire and Wixted 2011). Whereas free recall involves explicit access to a memory, recognition merely requires explicit identification of an option among a set of options. The point here is that while associations within interview data or forced-­ choice self-report survey data that were not explicitly identified by respondents themselves are interesting, this does not mean de facto that respondents would not recognize the associations as part of their beliefs or attitudes if presented to them as one option among many. Thus, this literature (Goldberg 2011; Boutyline 2017; Hunzaker and Valentino 2019; Taylor and Stoltz 2020) and the anthropological work upon which it builds (e.g., D’Andrade 1995) is based upon the false assumption that because an association was not explicitly identified by a respondent using free recall that it is an embodied, subconscious, implicit, and/or nondeclarative association. Thus, rather than being incorrect, these studies are incomplete. To verify claims that they have identified schemas, these scholars would need to begin by identifying associations between attitudes or beliefs in interviews or forced-choice self-report survey data, and then present respondents with these associations as an option of what they believe. If the respondent does not recognize the associations found in her/his own forced-choice self-report data or semi-structured interview data, then the researcher will have presented evidence that the identified association does not exist in the respondent’s declarative memory. A more efficient way to proceed is to develop tools that directly measure association in embodied, nondeclarative, unconscious, and/or implicit memory. I do exactly this in Chap. 7 as a way to demonstrate

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tools that can be used to identify nondeclarative schemas. Scholars could also use the measures of automatic processes discussed by Andrew Miles (Miles et al. 2019; Miles (2019). Thus, what is missing from the literature on schemas is evidence of schemas as implicit, automatic, embodied, and/or nondeclarative associations. This issue then echoes the misstep by Vaisey (Vaisey 2009; Vaisey and Lizardo 2010) in that these works all use forced-choice self-report surveys, or other types of methods, that actually elicit declarative memory and Type II processes while using these data to make claims about nondeclarative memory and Type I processes.

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CHAPTER 5

Theory: A Sociological Dual-Process Model of Outcomes

Introduction In this chapter, I argue that analytic dualism between Type I and Type II cognitive processes is supported by findings from psychology and neuroscience. Vaisey and Frye (2019) make the important observation that there is a need to replace the Cartesian Mind/Body dualism with another dualism that is more nuanced and empirically accurate. I argue that the findings I present in this chapter from neuroscience, and the subsequent dual-process model I build, provide one example of a new dualistic model of moral judgment and action that make the necessary improvements over the Cartesian Mind/Body dualism. Crucially, there has not been a sociological dual-process model that formally incorporates Type II cognition so as to make empirical predictions with data about the effects of Type II cognition and the interaction between Type I and Type II cognition. The dual-process model I build in this chapter will formally present a theory in which Type I and Type II processes affect decision-making separately and in which Type I and Type II processes also interact to affect action. My model then builds upon more recent work (Vila-Henninger 2015, 2020, 2021; Lizardo et  al. 2016; Miles et al. 2019) that argues that the interaction between Type I and Type II processes is important but does not create a formal model that advances these views. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 L. A. Vila-Henninger, Socialization, Moral Judgment, and Action, https://doi.org/10.1007/978-3-030-88278-5_5

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To proceed, I provide scope conditions for my theorization and then contextualize dual-process models in a broader decision-making context in order to build a dual-process model that accounts for all of the central elements of moral judgment. In particular, I use findings and theory from neuroscience, psychology, and sociology to develop a sociological dual-­ process of moral judgment that accounts for the temporal dimension of moral judgment as unfolding in a five-step process: socialization, stimulus/context, response, outcome, and justification (Haidt 2001; Greene et al. 2004; Vaisey 2009; Crockett 2013; Cushman 2013; Lizardo et al. 2016; Greene 2017; Lockwood et al. 2020; Vila-Henninger 2020, 2021). In this process, moral judgment and moral action constitute a “Response.” I refer to my dual-process model as the “Sociological Dual-Process Model of Outcomes” (DPMO) because it is a dual-process model that incorporates this temporal dimension of moral judgment and action in order to tie moral judgment to the outcomes of said judgment. I then discuss the Type I and Type II processes that are within the scope of the Sociological DPMO. Finally, I provide a discussion of how this model applies to political behavior and justification.

Scope Conditions As noted by Lizardo et al. (2016), different dual-process models from different areas have different scope conditions. Building on the work of Haidt (2001), the sociological dual-process model literature (Vaisey 2009; Vaisey and Lizardo 2010; Hoffman 2014; Vila-Henninger 2015, 2020, 2021; Moore 2017; Luft 2020) presents a dual-process model of moral judgment. This means that the sociological dual-process model only makes claims about moral judgment and processes that are linked to such judgment. Important recent work in sociology focuses on issues that are of relevance to the sociological dual-process model—such as socialization and attitudes (e.g., Vaisey and Lizardo 2016; Kiley and Vaisey 2020; Brett and Miles 2021) and measurement of automatic processes (Miles et al. 2019; Miles 2019). However, a key element of both of these lines of literature is that their measures are not specifically linked to moral judgment. While these works provide important insights into attitudes, preferences, behaviors, and “thinking dispositions” (Brett and Miles 2021), the empirical work in these articles does not clearly establish measures of moral judgment and then link these measures to the attitudes, preferences, behaviors,

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and “thinking dispositions” that they measure. Thus, while this literature provides important insight into socialization and different types of cognitive processes, the findings of this work are beyond the scope of the sociological dual-process model of moral judgment. In this chapter, I will therefore outline my model as it relates to moral judgment and dual-process models of moral judgment. I will then link my analyses (Chaps. 6 and 7) to moral judgment. My analyses will then incorporate insights from the aforementioned literature in a way that directly links it to dual-process models of moral judgment.

The Decision-Making Context: Socialization-­Stimulus/ Context-Response-Outcome-Justification To understand the decision-making process context in which moral judgment occurs and how moral judgment is related to behavior, we need to use Lizardo et al.’s (2016) review of the dual-process model literature— which creates a framework of the shared characteristics of dual-process models that span different subject matter and disciplines to create a “dual-­ process framework” (DPF). This is useful because my theory-building process requires an overarching framework of the shared elements of dual-­ process models that will then help us to understand the different stages in the causal process of decision-making. I develop Lizardo et al.’s (2016) Dual-Process Framework (DPF) using findings about different steps in the decision-making process from neuroscience and psychology (e.g., Greene 2017). Here, I am specifically referring to the “stimulus-response-outcome” model of action (Greene 2017). These three stages of “stimulus-response-outcome” are all key steps in the decision-making process and need to be integrated into the DPF in order to improve our understanding of dual-process models. Therefore, the “stimulus-response-outcome” framework helps to contextualize every dual-process model and helps us understand its different components as they evolve in the process of decision-making. However, I argue that the “stimulus-response-outcome” framework lacks two fundamental components of decision-making: socialization and post hoc justification. Socialization is a key part of dual-process models in neuroscience (e.g., Crockett 2013; Cushman 2013; Greene 2017;

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Lockwood et al. 2020); however, it is not incorporated into the psychological model of “stimulus-response-outcome.” Furthermore, a key element of dual-process models of moral judgment in psychology (Haidt 2001) and sociology (Vaisey 2009; Vaisey and Lizardo 2010) is the insight about post hoc justification as attempting to create social acceptance of an actor’s moral judgment. I therefore integrate these two insights into the “stimulus-response-outcome” model to expand the decision-making model from neuroscience and psychology (e.g., Greene 2017) to include socialization and justification. Thus, this “socialization-stimulus/context-response-outcome-justification” model helps to account for the five central elements of decision-making discussed in dual-process models of moral judgment. Here, moral judgment and moral action constitute the “Response” step.

The Dual-Process Model of Outcomes Next, I outline my dual-process model of moral judgment. To begin, work in sociology on dual-process models has excluded “outcomes” from their models. As Lizardo et  al.’s (2016) Dual-Process Framework (DPF) reveals, dual-process models often stop at theorizing and analyzing individual action. However, Lizardo et al.’s (2016) review excludes a key line of research on dual-process models from neuroscience. This literature from neuroscience extends the DPF beyond individual action to allow for the analysis of outcomes. Sociologists have largely ignored work in neuroscience on dual-process models of moral judgment—a gap that has been highlighted over the past five years (Vila-Henninger 2015, 2020; Luft 2020). Work from neuroscience (Crockett 2013; Cushman 2013; Greene 2017) posits “that dual-­ process moral psychology, and dual-process psychology more generally, are best explained in terms of the more basic computational distinction between model-based and model-free algorithms for learning and deciding” (Greene 2017: 69). This model is explained as “framing a dual-­ system theory of decision making in terms of action-and outcome-based value representations” (Cushman 2013: 285). I dub this approach from neuroscience as a “dual-process model of outcomes” (DPMO). This framework combines models of learning and decision-making from computational neuroscience for understanding behavior using a “stimulus-response-outcome” framework (e.g., Cushman 2013: 276–9) with a model of goal-oriented action from moral philosophy (Cushman

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2013: 275) that draws on the classic “means/ends” framework (Cushman 2013: 283). The result is a model that discusses moral reasoning in relationship to “outcomes”—or the consequences of behavior (Cushman 2013: 274, 279; Greene 2017: 69). The DPMO begins with understanding cognition and behavior using the “stimulus-response-outcome” model—in which the outcome can be positive or negative. I refer to cognition in this model as “outcome cognition.” Machine learning research in this area (summarized in Cushman 2013: 276–7) has revealed two classes of response. These two classes correspond to Type I and Type II outcome cognition in humans (Balleine and O’Doherty 2009; Dayan 2012; see Crockett 2013). Type I cognition in this domain, “Model-Free Reinforcement Learning” (MFRL), is developed through experience with associations between stimulus, response, and either a positive or negative outcome. Based on these experiential associations, the learner automatically attributes positive or negative values to a behavioral response, which are then stored in nondeclarative memory. This then generates automatic evaluations of the prospect of future action. These evaluations take the form of a gut “feeling” (Greene 2017: 69) that automatically drives the actor to execute or avoid a given behavior (Crockett 2013; Cushman 2013; Greene 2017; Lockwood et al. 2020) (Fig. 5.1). Type II cognition in this domain, “Model-Based Learning” (MBL), connects the knowledge of the outcomes for a range of possible responses— or series of responses—to a stimulus or set of stimuli. Based on this knowledge, it “builds” a causal model of the “stimulus-response-outcome”

Stimulus (e.g. Social Interaction)

Type I Outcome Cognition (MFRL)

Automatic Evaluation

Automatic Response: Perform Behavior Automatic Response: Avoid Behavior

Fig. 5.1  Model of Type I outcome cognition in the neuroscience dual-process model of outcomes

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process stored in declarative memory  and reasons using this model to select the path that maximizes the positive outcome—or reward. MBL is especially useful in complex environments that present a variety of stimuli and responses (Crockett 2013; Cushman 2013; Greene 2017; Lockwood et al. 2020). This process then relies upon individual-level “reasoning and planning” (Greene 2017: 69), in which the actor uses “an understanding of how the world works to identify a sequence of actions that will get one to one’s goal to decide on actions in order to achieve the outcome” (Greene 2017: 69). The work in neuroscience takes the DPMO a step further by applying it to goal-oriented decision-making. It does so by using a “means/ends” framework in which “action” is behavior that serves as a “means” to achieve an “end.” The DPMO expands the “means/ends” framework in order to analyze “hierarchically organized behavior” (Cushman 2013: 281), using the example of the famous moral dilemmas presented in the “trolley problem.” The DPMO integrates five concepts from moral philosophy (Goldman 1971; Mikhail 2011): “expected outcome,” “superordinate goal,” “subordinate goal,” “goal attainment,” and “side effect.” The “expected outcome” is the ultimate anticipated consequence of behavior. This outcome is defined by the “superordinate goal,” which is the “end” that the actor is attempting to achieve. A “subordinate goal” is a more immediate end generated so that one may execute an immediate means that ultimately serves to accomplish the superordinate goal (for a review of the psychological literature on this process see Cushman and Young 2011). “Goal attainment” is the achievement of the “superordinate goal” in order to produce the “expected outcome.” Finally, a “side effect” is an outcome that does not play a causal role in achieving the superordinate goal (see Cushman 2013: 275, 281–3). The DPMO work in neuroscience integrates the framework from moral philosophy with the “stimulus-response-reward” model in order to conceptualize the “superordinate goal” as the “reward.” For the DPMO, a stimulus triggers a response from an actor in which the reward, or superordinate goal, is pursued through the means of achieving the subordinate goals necessary for goal attainment—regardless of the side effects (Fig. 5.2). Finally, in this model from neuroscience (for a review see Greene 2017), Type I and II processes are brought together by Type II deliberation— defined in this model as “[cognitive] processes [that] are flexible and integrative in the sense that they involve a conscious and controlled

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Stimulus (e.g. Social Interaction)

Type II Outcome Cognition (MBL)

GoalOriented Decision

GoalOriented Action (Subordinate Goal)

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Goal Attainment: Expected Outcome, Superordinate Goal Side effect: Unexpected Outcome of Goal Attainment

Fig. 5.2  Model of Type II outcome cognition in the neuroscience dual-process model of outcomes

consideration of multiple inputs… [although] some of these inputs are ‘fast,’ inflexible, and often decisive” (Greene 2017: 68; Cushman 2013). This cognition is triggered when a stimulus triggers both MFRL and MBL cognition—thereby activating a cognitive process for “adjudicating” competing inputs from MFRL and MBL cognition and subsequently deciding upon an action (e.g., Greene et al. 2004: 396). As Greene (2017) explains, the simplest model would be a rat performing some task (an “action”) in order to receive a reward—an expected positive outcome. The stimulus would then be the cue that indicates the action will result in the expected positive outcome. Cushman (2013) applies the DPMO to the “trolley problem,” which presents actors with stimuli in the form of moral “dilemmas.” In the “footbridge” case, the actor must solve the dilemma by pursuing the “subordinate goal” of harming the bystander by performing the “action” of pushing the bystander off the footbridge to stop the trolley. This action would then result in the attainment of the “superordinate goal” in the expected outcome of saving the passengers on the train. In the “trolley case,” the actor must solve the moral dilemma by “acting”—in this case, pulling the lever. This action would then reach goal attainment by achieving the superordinate goal and producing the expected outcome of saving the passengers on the trolley. This action also has the side effect of killing the bystander on the other track. The mystery from experiments that required respondents to generate hypothetical solutions (Greene et al. 2004) was why respondents tended to behave differently depending on the context—despite the fact that the

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Type I Outcome Cognition Complex Stimulus (e.g. Moral Dilemma, Social Interaction)

Automatic Evaluation

(MFRL)

Type II Outcome Cognition

Type I and Type II Input Integration

GoalOriented Decision

(MBL)

Fig. 5.3  Model of integrative outcome cognition in the neuroscience dual-­ process model of outcomes

moral goal remained the same (saving five lives at the expense of one). The answer is that for most people the subordinate goal of pushing the man off the footbridge triggers a negative automatic response from Type I cognition, which is favored by integrative processes over the Type II goal pursuit of saving the passengers on the train. However, when respondents can flip a switch to kill the bystander—making the bystander’s death a side effect instead of a subordinate goal—integrative processes tend to favor Type II goal pursuit of saving the people on the train over the Type I generated negative automatic response to killing the bystander (Fig. 5.3).

Dual-Process Model of Outcomes Dual-Process Model

and the Sociological

There are some important similarities and differences between the DPMO from neuroscience and the sociological dual-process model. First, Type II cognition in the DPMO is distinct from the sociological dual-process model’s conceptualization of Type II cognition as primarily used for justification and having little or no effect on behavior (Vaisey 2009; Vaisey and Lizardo 2010). A further distinction is the timeframe—as Type II cognition in the neuroscience DPMO occurs in the “response” phase and the sociological dual-process model’s post hoc Type II justification occurs in the “justification” phase. Moreover, Type II cognition in the DPMO

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appears to be analogous to Bourdieu’s description of conscious processes overriding dispositions (Bourdieu and Wacquant 1992). Furthermore, the element of Type II integrative cognition in the DPMO that deliberates between Type I and Type II inputs helps to extend the sociological dual-process model. This process seems to be dismissed by Bourdieu (Bourdieu and Wacquant 1992: 137) and has yet to be formally incorporated into sociological dual-process models (Vaisey 2009; Vaisey and Lizardo 2010). However, developing a model that does so would constitute a key contribution, as many have remarked the importance of incorporating deliberation between Type I and Type II processes into sociological dual-process models (Vila-Henninger 2015; Lizardo et  al. 2016; Moore 2017; Miles et al. 2019; Luft 2020; Mohr et al. 2020). Moreover, since Type I “Model-Free Reinforcement Learning” is the only type of cognition from the DPMO that aligns with the sociological dual-process model (Vaisey 2009; Vaisey and Lizardo 2010), it is worth comparing and further developing our understanding of these processes. To begin, a foundational framework for the sociological DPM’s concept of “practical consciousness” in sociology is Bourdieu’s “habitus.” “Habitus” is defined as “systems of durable, transposable dispositions,” that is “produced” by the “conditionings associated with a particular class of conditions of existence” and “are the basis of the perception and appreciation of all subsequent experiences” (Bourdieu 1990: 53–54). Subsequently, for Bourdieu, “being the product of a particular class of objective regularities, the habitus tends to generate all the ‘reasonable’, ‘common-sense’, behaviors (and only these) which are possible within the limits of these regularities” (Bourdieu 1990: 55). These reactions are automatically generated without the reflection of subjects (Bourdieu 1984: 170, 466, 474). Finally, for the habitus, “[s]timuli do not exist for practice in their objective truth…acting only on condition that they encounter actors conditioned to recognize them” (Bourdieu 1990: 53). This model has several important elements that have been empirical corollaries. The habitus is (1) produced by “regularities” or “conditionings,” that is, repeated exposure to material conditions, (2) a system of “transposable dispositions” that facilitate automatic interpretation and subsequently, (3) the interpretation and response to stimuli to which it is conditioned to recognize and respond, and (4) automatically generated behaviors that are “reasonable” given its conditions of repeated exposure. For the sociological dual-process model, moral “schemas” are a form of “practical consciousness” that operate through “habits of judgment and

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evaluation” (Vaisey 2009: 1683), are equivalent to “habitus” (Vaisey 2009: 1687), and are stored in nondeclarative memory (Vaisey and Lizardo 2010). Subsequent research emphasizes that this practical consciousness is developed through “repeated” “exposures,” “experiences,” and “practice” (Lizardo et  al. 2016: 293–5). This stands in contrast to other measures that have operationalized habitus using attitudinal measures (e.g., Gaddis 2013). The definition of DPMO Type I “Model-Free Reinforcement Learning” (MFRL) overlaps considerably with the definitions of habitus from Bourdieu, as well as to the sociological dual-process model’s concept of “practical consciousness” (Vaisey 2009; Vaisey and Lizardo 2010). However, MFRL is distinct from habitus because MFRL’s scope is moral judgment and habitus’ scope is taste. Yet the similarities are striking. Recall that DPMO Type I MFRL is based on experiential learning and automatically attributes positive or negative values to stimuli based on prior outcomes. Type I MFRL then generates automatic responses to current stimuli and expected outcomes given its conditioning. The resulting automatic responses can often divert the respondent from achieving the superordinate goal—thereby failing to produce the expected outcome (Cushman 2013; Greene 2017). Furthermore, we must note that MFRL does not rely on implicit goals, but is developed through conditioning (Wood et al. 2021). MFRL is automatic in the sense that it is encoded in procedural memory as habit (Greene 2017; Wood et  al. 2021). Here, we see Lizardo’s (2017) model that emphasizes dissociation between Type I and Type II processes in socialization (see also Lizardo et al. 2016) as providing key insight regarding the separation of socialization processes into Type I (nondeclarative) and Type II (declarative). MFRL is persistent even when goals change (Greene 2017)—thus supporting the case that MFRL develops habitual responses through procedural memory. This builds on work from Wood et al. (2021) on the distinction between habit and goal-oriented behavior as dissociable. Thus, we see that work in neuroscience on MFRL and its differences from MBL is reaffirmed by work in the psychology of habit (for a summary, see Wood et al. 2021).

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Differentiating Between Types of Automatic Cognition However, when discussing the similarities between schemas and MFRL, we run into a key limitation in the literature. Work on dual-process models (Lizardo 2017; Miles et al. 2019) has tended to lump all nondeclarative or automatic Type I processes into the same category. Here, I make an important contribution by drawing upon the memory literature (e.g., Squire 2004) to differentiate between different nondeclarative Type I automatic processes  and by doing so  build on recent  critiques of the schema literature (Boutyline and Soter 2021; Leschziner and Brett 2021). Before we begin, however, we must note that the recent introduction by Lizardo (2021) of a “third” form of personal culture (beyond declarative and  nondeclarative culture)  that he calls  “knowledge-what” is not supported by the memory literature in cognitive science. Rather than a distinct type of culture or memory, “knowledge-what” actually corresponds to semantic memory (e.g.  Markowitsch 2000; Squire 2004; Salmon and Squire 2009; APA 2021, also see Chap. 4), which is a type of declarative memory. As such, “knowledge-what” is a form of declarative culture and the two established forms of personal culture (declarative and nondeclarative) remain. We begin with the definition of declarative versus nondeclarative memory. Squire (2004) defines declarative memory as “representational. It provides a way to model the external world, and as a model of the world it is either true or false” (Squire 2004: 173). This is key, because in contrast, nondeclarative memory “is neither true nor false. It is dispositional and is expressed through performance rather than recollection” (ibid.). With this in mind, Squire (2004) distinguishes between four different types of nondeclarative memory: (1) “Procedural (Skills and Habits),” (2) “Priming and Perceptual Learning,” (3) “Simple Classical Conditioning,” and (4) “Nonassociative Learning” (Squire 2004: 173, esp. Figure 1). For this book, I focus on the difference between Procedural Memory on the one hand and Priming and Perceptual Learning on the other. Procedural memory, referring to habits and skills, is defined as “a wide variety of skill-based kinds of learning” (Squire 1992: 233). Furthermore, “habit” is defined as automatic responses to reoccurring stimuli—or cues—that occur despite individual short-term goals or instances of adverse outcomes for a previous instance of habitual behavior (Wood and Runger 2016; Wood et  al. 2021). Procedural memory is the primary

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neural substrate of the automatic elements of habit (Wood et  al. 2021) and automatic habitual responses are the primary mechanism of MFRL (Greene 2017). Conversely, Priming and Perceptual Learning is a form of memory that “refers to the improved facility for detecting or processing a perceptual object based on recent experience…[and] can involve the acquisition of new information” (Squire 1992: 234). As we will see based on the literature on schemas that I review below, Priming and Perceptual Learning is likely the form of nondeclarative memory in which schemas are encoded. Thus, we must distinguish the concept of “schemas” on the one hand from habitus, habit, MFRL, and practical consciousness on the other in terms of the type of nondeclarative memory in which they are encoded. Early work on the dual-process model argues that cultural schemas are “largely unconscious networks of neural associations that facilitate perception, interpretation, and action” (Vaisey 2009: 1686). From this perspective, schemas are “embodied and durable” (Vaisey and Lizardo 2010: 1599, italics in original). Recall that scholars likened schemas to habitus (Vaisey 2009; Goldberg 2011: 1410), yet also define schemas as “not clear sets of behavioral rules but rather implicit recognition procedures that emerge from intricate associational links among salient aspects of our cognitively represented experiences (D’Andrade 1995)” (Goldberg 2011: 1401). However, in subsequent work, we have seen a delineation of schemas as “a form of nondeclarative memory (Squire 1992, 2004)—acquired, used, and altered through a repeated, automatic process of schematization from experience” (Wood et al. 2018: 246). Scholars have since ceased to claim that schemas are embodied, instead defining them as “a set of associations between concepts in memory acquired from experience and used for the purposes of categorization, recognition, and filling-in of missing information” (Mohr et al. 2020: 44). Key work has since noted the ambiguities in the uses of the term “schema” in sociology and astutely  critiqued how sociologists employ this concept (Boutyline and Soter 2021; Leschziner and Brett 2021). Crucially, work in neuroscience does not define schemas as being encoded in procedural memory—a form of nondeclarative memory associated with habit and embodiment that is based on repeated physical experiences and skills (Squire and Wixted 2011). Instead, they acknowledge that there is much debate about the use of the term and argue that the “general consensus among researchers is that schemas are associative,

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superordinate knowledge structures that represent abstracted commonalities across a number of instances” (Kan et al. 2020: 1; see also Ghosh and Gilboa 2014). Therefore, definitions of schemas from more recent sociological literature, as well as from recent neuroscience, outline a concept of schemas that shares much in common with the definition of Priming and Perceptual Learning. Extending to the more classic definitions of schemas in the sociological dual-process model literature (Vaisey 2009; Vaisey and Lizardo 2010), aside from being labeled as embodied, the rest of Vaisey’s schemas definitions—especially as neural networks based in experience—align more closely with the definition of Priming and Perceptual Learning than with Procedural Memory. Thus, we see in the literature on neuroscience a rift between different definitions of the term schema—yet schemas are largely not defined as embodied or processed through procedural memory. We therefore need to make a key theoretical distinction between different types of nondeclarative memory. Following the literature in neuroscience, then, I make the distinction between habit, procedural memory, practical consciousness, habitus, and MFRL on the one hand and schemas on the other in terms of the nondeclarative memory in which they are encoded. Finally, it is important to disentangle the term “embodied” from “procedural memory.” While the term “embodied” has been used to refer to “practical” consciousness or schemas (e.g. Vaisey and Lizardo 2010), as it is used in cognitive linguistics, “embodied” cognition is “conceptual knowledge is…mapped within our sensory motor system…[that] not only provides structure to conceptual content, but also characterizes the semantic content of concepts in terms of the way that we function with our bodies in the world” (Gallese and Lakoff 2005: 456). This finding has been reaffirmed by qualitative research in culture and cognition on embodied metaphors (e.g., Ignatow 2009; Winchester 2016).

Type I and Type II Processes and the Sociological DPMO Now that we have a framework for the overall process of decision-making, and have also outlined a dual-process model that fits this framework, we can further discuss Type I and Type II processes and their role by providing a temporal dimension to the dual-process model. The key

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contribution of the “socialization-stimulus/context-response-outcome-­ justification” framework is that it provides a set of stages in the decision-­ making process in which we can situate different functions of Type I and Type II. Lizardo et al. (2016) already begin to do this, but only provide a typology for understanding different stages of dual-process models relative to cultural socialization—or “enculturation.” I argue that rather than using cultural socialization as the primary reference point, we can separate this process into five distinct stages that all have equal importance. The key reason for doing this is that it helps us to reconcile competing models. For example, Lizardo (2017) argues for a dual-process model in which Type I and Type II processes are dissociable rather than in conflict—contrary to work on dual-process models of moral judgment (Haidt 2001; Vaisey 2009; Vaisey and Lizardo 2010; Vila-Henninger 2015). Furthermore, Vaisey (2009) argues for Type II processes as involved in justification rather than in decision-making. With the aforementioned five-step process (socialization-stimulus/context-response-outcome-­ justification), we can contextualize and reconcile these models. Lizardo’s (2017) model makes sense when we understand socialization processes—which are generally characterized by two distinct types of memory: nondeclarative (Type I) and declarative (Type II)  (e.g. Squire 2004). However, Lizardo’s (2017) model in which there is little to no interaction between Type I and Type II processes does not apply when we examine moral judgment and decision-making—in which neuroscience has long established that actors often deliberate between Type I and Type II processes (Greene et al. 2001, 2004; Greene 2007; Paxton et al. 2012; Greene 2007; Lockwood et  al. 2020—for a sociological application see Vila-Henninger 2015, 2020, 2021; Luft 2020). Furthermore, here it is important to note that when we use the full context of socialization-stimulus/context-response-outcome-justification, we can see that Haidt’s (2001) and Vaisey’s (Vaisey 2009; Vaisey and Lizardo 2010) dual-process models of moral judgment that emphasize Type II processing as social justification are not in conflict with the DPMO, but rather are complimentary. While Haidt and Vaisey over-­ emphasize automatic processes (Leschziner 2019) and over-emphasize justification, when we identify these as different stages in the process of moral judgment and action, we see that conflicting theories actually emphasize different parts of a larger process. Thus, following the work of Greene (e.g., 2017), we see that in the “response” phase, Type I and Type II processes can both separately  drive moral judgement, and  Type II

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processes can adjudicate between  competing MBL and MFRL inputs. Subsequently, Type II as providing justification is not a competing element, but rather a complementary component that happens after the response and/or outcome.

Summary of Sociological Dual-Process Model of Outcomes Now that we have covered the sociological dual-process model of outcomes, I outline the process through which I see this model operating. I argue that the process is as follows using my “Socialization-Stimulus/ Context-Response-Outcome-Justification” framework for understanding the decision-making process: 1. Socialization: Social structure shapes collective and/or external cultural elements (e.g., Lizardo’s 2017 “public culture”). Actors draw upon these elements during social interaction  or instruction (Guhin et al. 2021; Lizardo 2021). Through this social interaction or instruction, actors internalize different cultural elements. These learned elements of culture then affect action, for example, by driving decision-making (Vaisey 2009) or limiting possible courses of action in future social interaction (Swidler 2001). 2. Stimulus/Context: The actor is then faced with an immediate social context—which sometimes involves moral dilemmas (e.g., Cushman 2013; Greene 2017). 3. Response: The primary element of “Response” in this model is moral judgment and moral action. The actor responds using hierarchically organized goal-oriented behavior, internalized elements of culture are processed through Type I MFRL, Type II MBL, or Type II “integrative” outcome cognition. Type I MFRL automatically generates behavioral responses to environmental cues or subordinate goals, often causing a behavioral deviation from the superordinate goal. Type II MBL cognition is goal-oriented—often using subordinate goals and corresponding actions as means to achieve a superordinate goal. This type of cognition uses a causal representation of the environment in order to select subordinate goals and actions that are supposed to enable it to achieve its superordinate goal. Type II “Integrative” outcome cognition is activated in complex or difficult social interactions

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(the definition and scope of these interactions are discussed in neuroscience and beyond the theory and analysis of this book: see, e.g., Greene et al. 2004). This Type II integrative cognition receives inputs from Type I MFRL and Type II MBL cognition, deliberates, and then favors one or the other type of response. 4. Outcome: These are the consequences of the actor’s “Response” (Greene 2017). Outcomes are often social and therefore shape and/or reproduce social structure. 5. Justification: Actors then justify their responses and the outcomes of their responses post hoc (Haidt 2001; Vaisey 2009)—often in order to assure the social acceptability of their response and its outcome.

Application: Political Socialization and Legitimation of Everyday People It is important to note that dual-process models each have a specific application and thus scope conditions (Smith and DeCoster 2000; Lizardo et al. 2016)—which in the case of the DPMO both in neuroscience and sociology is moral judgment. In this vein, I will synthesize dual-process models of moral judgment from moral psychology, neuroscience, and sociology with work on rationalization, legitimacy, and political socialization to create a dual-process model of political socialization and justification. This section then conceptualizes political justification as legitimation and as a Type II process, and theorizes its link to political socialization via moral political judgments. In what follows, I divide up moral political decision-making of everyday people according to my model into the five aforementioned steps: socialization, stimulus/context, response, outcome, and justification.  For an article length discussion, see Vila-Henninger (2020). Socialization: We can divide the actions and effects of political regimes into Type I and Type II activities. Type I activity is practice. Political regimes’ practices implicitly establish or reproduce the power of the corresponding regime. Furthermore, Type II activity is goal-oriented decision-­making, as well as elite and public discourse concerning a political regime’s goals and/or models of the world that allow one to pursue a goal of a political regime. These goals and/or models establish, justify, reaffirm, and/or reproduce the power of the corresponding political

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regime and lead to goal-oriented decision-making behavior that complies with said power. This results in Type I political socialization processes and Type II political socialization processes. Type I and Type II socialization processes are the product of policy, institutions, and social structure. Practices are internalized through Type I Model-Free Reinforcement Learning and goals and/or models communicated through elite and social goal-oriented decision-making and discourse are acquired through Type II Model-Based Learning. Stimulus/Context: For context and political stimuli, actors are embedded in a political system, by which I mean a political “regime” or “a rule governed system of positions, relations between positions and position-­ specific acts” (Walker 2014: 360; see also Weber 1978 [1924]). For this theory-building description, I use the term “political system” to describe an entire political regime, a subset or component of a political regime (such as political policy, institutions, and social structures), and “position-­ specific acts” (Walker 2014: 360). This then includes the political activity of everyday people. Specific actions within a regime then provide the political context to which everyday people respond. Response: Everyday people’s political Type I MFRL reproduces practices or develops practices based on different elements of a political regime or regimes that create or reaffirm/reproduce the perception of the consensus about compliance with the power of the regime(s). Everyday people’s political Type II MBL is goal-oriented decision-making that follows corresponding models from elite and/or public discourse that the regime produces. Actors then deliberate between impulses from Type I and Type II socialization when faced with contextual dilemmas that trigger Type I and Type II responses. Outcome: The Type I MFRL practices mentioned in the previous section (“Response”) create or reaffirm/reproduce the perception of the consensus about compliance with the power of the policy, institution, and/or social structure. Deviating from the practices mentioned in the previous section (“Response”) in the context of a regime then serves to undermine the behavioral perception of consensus regarding compliance with the power of a political regime. Furthermore, Type II MBL goal-­ oriented decision-making mentioned in the previous section (“Response”) creates or reaffirms/reproduces the perception of the consensus about compliance with the power of the policy, institution, and/or social structure. Deviating from these goals and models in the corresponding policy,

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institutional, and/or social structural context then serves to undermine the behavioral perception of consensus of compliance with the power of a political regime. Justification: Everyday people’s political Type II processes are then triggered in legitimation/rationalization processes of actions and/or the outcomes of actions. Type II rationalization of Type I and/or Type II political activity—regardless of the actor—draws upon Type II policy, institutional, and/or social structural discourse regarding goals and models of the world in which these goals can be achieved. As mentioned, these goals and models create or reaffirm/reproduce the perception of consensus about compliance with the power of the political regime. Actors engage in legitimation to comply with social pressure, to reaffirm prior beliefs driven by group loyalties—including partisan allegiances, to transfer information, in response to moral intuitions, out of a desire for the consonance of attitudes and behaviors, a desire to “sound rational” or accurate and avoid cognitive dissonance, and/or out of a feeling of existential or social threat—which often results in a defense of the status quo. Motives are likely learned through socialization. Actors are often unaware of these motives or unable to understand them. Thus, through this process, goal-oriented behavior is refined through the rationalization of goal-­ oriented action, while the rationalization of practice develops information transfer to refine and improve goal-oriented Type II cognition. This then often helps to improve the rationalizer’s chances of survival or social success. The key here, though, is that legitimation draws upon a political regime’s goals and models of the world that were communicated through a regime’s elite and/or public discourse and internalized through Type II socialization processes by the public. Everyday people legitimate a political regime by drawing upon Type II public or elite discourse produced by a political regime about goals and models of the world that correspond to said goals. These goals and corresponding models of the world are then norms, values, and/or widely held beliefs that were either created by the regime or used by the regime to create or reproduce/reaffirm the perception of a consensus about compliance with its power.

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CHAPTER 6

Analysis Using Forced-Choice Self-Report Survey Data (National Study of Youth and Religion Waves 1 and 4)

Introduction In this chapter, I build upon the sociological dual-process model (Vaisey 2009; Vaisey and Lizardo 2010; Hoffmann 2014; for a summary, see Lizardo et al. 2016). This model argues that through cultural interaction individuals develop moral “schemas”—or unconscious neural networks of associations built through experience (Vaisey 2009: 1686) that are equivalent to “habitus” (ibid.: 1687)—that automatically generate moral intuitions that “drive” action-oriented judgments concerning deviant or prosocial behavior (ibid.: 1698). Reasoning in this model, conversely, is generated by post hoc “deliberative” cognition (ibid.: 1681)—“when required by social demands” (ibid.: 1687)—to justify judgments and actions driven by these automatic moral intuitions. For these scholars then, reasoning is largely inconsequential for predicting behavior. The key here, however, is that neither this model nor subsequent work in the sociology of culture has addressed how deliberative (Type II) cognition is predictive of outcomes or how deliberation between competing Type I and Type II cognition is predictive of outcomes (Vaisey 2009; Lizardo and Strand 2010; Martin 2010; Martin and Desmond 2010; Vaisey and Lizardo 2010; Abramson 2012; Leschziner and Green 2013; Hoffmann 2014; Patterson 2014; Miles 2014, 2015; Lizardo et al. 2016; Winchester 2016; Lizardo 2017; Moore 2017; Stoltz and Lizardo 2018; Miles et  al. 2019; Brett and Miles 2021). By this, I mean that while © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 L. A. Vila-Henninger, Socialization, Moral Judgment, and Action, https://doi.org/10.1007/978-3-030-88278-5_6

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scholars have recognized that Type II processes and the interaction between Type I and Type II processes can affect behavior (e.g., Vila-­ Henninger 2015, 2020, 2021; Lizardo et al. 2016; Miles et al. 2019; Luft 2020; Mohr et al. 2020), scholars have yet to build a formal model that integrates these insights and applies them empirically. In Chap. 5, I used recent scholarship from neuroscience to develop a sociological “Dual-Process Model of Outcomes” (DPMO) that synthesizes work from sociology and cognitive science. This model provides a framework for theorizing the connection between cognitive processes involved in socialization and moral judgment on the one hand, and outcomes of moral judgments on the other. In this chapter, I apply this model to develop and test novel measures of the cognitive processes from my Sociological Dual-Process Model of Outcomes: Type II Model-Based Learning (MBL), Type I Model-Free Reinforcement Learning (MFRL), and Type II Integrative Processes/Deliberation Between Competing MBL and MFRL Inputs (Integrative Processes). Using recent scholarship from neuroscience, as well as the psychology of habit, I develop operationalizations of Type I MFRL, Type II MBL, and Type II Integrative Processes in longitudinal data from the National Study of Youth and Religion (NSYR). In particular, I develop indicators of cognitive processes that drive moral judgment that are learned through moral and religious socialization. In support of my sociological DPMO, I find consistent evidence that indicators of Type I MFRL, Type II MBL, and Type II Integrative Processes measured at Wave 1 (respondents ages 13 and 17) are predictive of respondent reports of incarceration approximately ten years later (Wave 4). This book’s empirical framework then allows us to use a dual-process model with certain  forced-choice self-­ report  survey items to demonstrate how different forms of socialization and moral judgment  receive differential treatment from the criminal justice system by building on similar quantitative analyses (e.g., Silver et al. 2020). A key contribution here is my development of operationalizations of Model-Based Learning (Type II), Model-Free Reinforcement Learning (Type I), and Integrative Processes/Deliberation Between Competing MBL and MFRL Inputs (Type II) using forced-choice self-report data. In particular, I use findings from neuroscience to reinterpret Vaisey’s (Vaisey 2009, Vaisey and Lizardo 2010) schema variables. Furthermore, building on the psychology of habit, I use forced-choice self-reported survey data on behavior frequency to develop measures of Type I MFRL—which is stored in procedural memory rather than in Priming and Perceptual Learning (Greene 2017).

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Background Stephen Vaisey’s (Vaisey 2009; Vaisey and Lizardo 2010) sociological dual-process model argues that two independent cognitive processes are most relevant for understanding moral judgment and behavior. The first process is automatic cognition and operates subconsciously via “schemas” to motivate moral action (Type I). The second process is discursive (Type II) and largely does not affect behavior. Vaisey then created “forced-choice surveys” that were then implemented in an attempt to force respondents to “draw disproportionately on practical consciousness” (Vaisey 2009: 1688) and therefore measure these subconscious schemas and their association with future behavior. Vaisey used the first two waves of the NSYR survey data on youth religious attitudes, collected in 2002 and 2005 (Vaisey 2009: 1690), as well as in-depth follow-up interviews of a sample of these respondents from each wave, to test his model. Vaisey (2009) created two hypotheses (1690): (1) that because conscious cognition is not strongly involved in everyday moral decision-making, interview responses will not provide a coherent explanation for moral decision-making; (2) practical consciousness/habitus will provide a predictive measure for moral decision-­making. Vaisey then used Bellah et al.’s (1985) four-part moral schema to create a survey question to attempt to measure schemas (Vaisey 2009: 1691) and a three-part coding system for the interview data. Vaisey argues (ibid.: 1694–5; 1698) that the interview data support claims that conscious, discursive moral reflection does not provide adequate justification for a respondent’s actions and is often contradictory or illogical. Conversely, Vaisey (2009) found that “the choice of a moral script in 2002 [or schemas] is a very good overall predictor of behavior in 2005, even controlling for network characteristics, religious participation, and demographic factors” (ibid.: 1703). This finding then supports Vaisey’s second hypothesis about the influence of internalized subconscious schemas on action. He concludes that surveys are important tools for measuring how meaning affects action, but that interviews are also important due to their ability to help researchers understand “how people ‘make sense’ of the world to each other and to themselves in the face of an inquisitive questioner” (ibid: 1705). This chapter presents the first empirical analysis of this book and extends Vaisey’s (Vaisey 2009; Vaisey and Lizardo 2010) analysis by using NSYR data from Waves 1 and 4. My investigation provides insight into

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how different types of moral and religious socialization and moral judgments receive differential treatment from law enforcement by analyzing, in part, how measures in the data that Vaisey used to measure moral schemas in Wave 1 are predictive of respondent incarceration record ten years later. Recall that I use the term “moral judgment” as it is defined scientifically instead of normatively. Thus, I use a definition of “moral judgment” from neuroscience: “evaluative judgments of the appropriateness of one’s behavior within the context of socialized perceptions of right and wrong” (Forbes and Grafman 2010: 304).

Research Questions I carry out my analysis to answer the following two research questions: RQ 1: Do DPMO outcome cognition variables measured in respondents ages 13–17 (Wave I) predict whether these respondents will be incarcerated—or spend time in some type of correctional facility—by the ages of 23–28 (Wave 4)? RQ 2: Do DPMO outcome cognition variables measured in respondents ages 13–17 (Wave 1) predict the number of times the respondent will be incarcerated—or spend time in some type of correctional facility—by the ages of 23–28 (Wave 4)?

I argue that “incarceration” is an appropriate dependent variable given that I am building upon Stephen Vaisey’s (Vaisey 2009; see also Hoffmann 2014) analysis of the connection between moral schemas and deviant behavior. I thus select this dependent variable because as the literature has established, deviant or anti-social behavior and dispositions serve as risk factors for youth incarceration—both in the US (e.g., Shader 2004; Reingle et al. 2013) and abroad (e.g., Ortega-Campos et al. 2016)—and prosocial orientations and positive relationships with adults serve as protective factors against incarceration (e.g., Shader 2004). Longitudinal analyses of this sort can quickly become very complex (e.g., Hoffmann 2014). For the sake of parsimony, I restricted my analysis to two waves and one dependent variable survey item. I did not test for mediation, moderation, or interactions in my analysis because my objective is to provide initial evidence that internalized elements of culture processed with DPM outcome cognition are empirically linked to outcomes of deviant behavior. By “DPM outcome cognition,” or Dual-­ Process Model outcome cognition, I am referring to one or more of the cognitive

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processes involved in the sociological dual-process model of outcomes: Type II Model-Based Learning, Type I Model-Free Reinforcement Learning, and Type II Integrative Processes/Deliberation Between Competing MBL and MFRL Inputs. Terminology is important here. For example, Vaisey (2009) uses the terms “behavior” and “outcome” interchangeably (e.g., ibid.: 1699). For Vaisey (ibid.), “action” concerning moral schemas is understood in a twofold manner: first as selection into social contexts and second as behavioral reactions in those contexts (ibid.: 1705). Within my Sociological DPMO, outcomes are the consequences of behavior, and “action” is a behavioral means to an end (for a review in the neuroscience literature, see Cushman and Young 2011; Cushman 2013; Greene 2017). My analysis will then apply these definitions from neuroscience and my Sociological DPMO. Conversely, it is important to notice that, counter to the claims to some (Lizardo et  al. 2016), if we apply the DPMO’s definitions we see that Vaisey (e.g., 2009) successfully extended Haidt’s (2001) dual-process model of moral judgment to a dual-process model of individual-level action. This is because Vaisey’s (2009) dependent variables were all means to achieving some end (except one dependent variable). To proceed with my analysis, I apply findings and definitions from psychology and neuroscience to operationalize and select data that indicate individuals’ use of DPM outcome cognition and allow me to construct corresponding variables using the NSYR Wave 1 data set. In particular, I offer a reinterpretation of Vaisey’s (2009) moral  “schema” variables as actually measuring Type II cognition/declarative memory  and  subsequently use the psychology of habit to create a framework for selecting and coding forced-choice self-report survey data on behavior frequency that I use to operationalize Type I MFRL.

Hypotheses My empirical agenda, then, is to develop indicators of each type of DPM outcome cognition in order  to find empirical associations with what the literature has established as a potential outcome of deviant behavior (e.g., Shader 2004): incarceration. Evidence of such associations will support the use of this model (the Sociological Dual-Process Model of Outcomes) for the study of the consequences of socialization and moral judgments. Extant work in this area has used longitudinal data to show associations between cognitive processes that drive  moral judgments  at a t0 and

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deviant behavior at t1 (Vaisey 2009; Hoffmann 2014). Extending this empirical framework, I operationalize indicators of each type of cognitive process that drives moral judgment  at t0 and investigate their empirical associations with outcomes of deviant behavior at t1. To build on this literature on the link between socialization/moral judgment  and deviant behavior, I chose respondent incarceration as the outcome—or behavioral consequence. I acknowledge that people are wrongly incarcerated and that there is much discrimination in the criminal justice system; however, incarceration serves as a useful—although imperfect—starting point for an empirical analysis of the outcomes of deviant behavior. To perform this analysis, I generated the following three formal hypotheses for analysis using longitudinal data. Hypothesis 1 Empirical indicators of Type I “Model-Free Reinforcement Learning” outcome cognition at t0 are associated with incarceration or the number of times incarcerated at t1. Hypothesis 2 Empirical indicators of Type II “Model-Based Learning” outcome cognition at t0 are associated with incarceration or the number of times incarcerated at t1. Hypothesis 3 Empirical indicators of Type II Integrative Processes/Deliberation Between Competing MBL and MFRL Inputs (or “Integrative Processes” for short) outcome cognition at t0 will be associated with incarceration or the number of times incarcerated at t1. Following Vaisey’s (2009) seminal article, my analysis uses the National Survey of Youth and Religion. Vaisey’s (ibid.) results are impressive because they demonstrate the effects of internalized cultural meanings— supposedly  in the form of moral schemas—in respondents ages 13–17 (NSYR Wave 1) on patterns of their deviant and prosocial actions three years later (Wave 2). I contribute by investigating the predictive effects of DPM outcome cognition on the outcomes of deviant behavior measured ten years later.

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Applying the DPMO to Using Forced-Choice Self-­Report Survey Data How do we apply the DPMO empirically using forced-choice self-report survey data? As Lizardo et al. (2016) discuss, analysts should stay within the scope conditions of the dual-process model they employ. Furthermore, it is important to identify correctly which dual-process model—and subsequent variables—should be used given the research question. Therefore, this analysis stays within the scope conditions of the Sociological DPMO: moral judgment. Crucially, every operationalization of DPMO outcome cognition in this study is a measure of the cognitive processes that are learned through socialization and likely drive moral judgment. Using the DPMO and our understanding of DPM outcome cognition, we can conceptualize DPM outcome cognition as a mediating process—or set of processes—that can be analyzed relative to “outcomes,” and therefore as part of the five-stage decision-making process that I outlined in Chap. 5. Recall that this process is Socialization-Stimulus/Context-­ Response-­ Outcome-Justification. As moral judgment is part of the “Response” step, DPM outcome cognition variables are measures of some of the cognitive processes that actors likely use during moral judgment. These processes should then be understood as being developed in the “Socialization” step but measured in the “Response” step. The DPM outcome cognition variables at t0 thus estimate how an actor’s socialization has influenced a cognitive process that is likely used by a respondent in her/his moral judgment. The associations between these variables at t0 and the incarceration variables at t1 then measure how these cognitive processes—which are likely involved in moral judgment and developed through socialization—are associated with, and likely have a causal influence on, outcomes of moral judgment and action. In general, then, cognitive variables that play a role in moral judgment should be selected according to their corresponding Type I and Type II processes. In the case of DPM outcome cognition, Type I MFRL would best be indicated by a cumulative life experience that would predispose individuals—through positive or negative reinforcement—toward or away from a subordinate or superordinate goal  and corresponding outcome. Type II MBL would then best be indicated by reasoning processes that use a causal model to pursue a superordinate goal and corresponding expected outcome. Type II Integrative Processes would be indicated by data that asks individuals to deliberate about a decision—or set of decisions—that triggers competing Type I MFRL and Type II MBL inputs.

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Data, Variables, and Operationalizations Data To apply this DPMO in such a way that helps us to understand socialization and the related DPM outcome cognition, I selected longitudinal data that would allow me to trace the effects of indicators of socialization in DPM outcome cognition in an initial wave to a likely outcome of moral judgment and action in a subsequent wave. I chose to analyze data from the National Study of Youth and Religion, which is a nationally representative longitudinal telephone survey of 3290 teenagers in the United States who were between 13 and 17 in the initial round. The survey consists of four rounds and was conducted in both English and Spanish. The first wave was conducted between 2002 and 2003, and Wave 4 was conducted approximately ten years later when respondents were between the ages of 23 and 28. As opposed to the first wave, 85% of the respondents in the fourth wave completed the survey online. The fourth wave collected data on 65% of those who participated in the initial wave, with an N of 2144. All of the independent and control variables in this article are from Wave 1 and the dependent variable survey item is from Wave 4. Dependent Variable For my analysis, I use a self-reported measure of instances of respondent incarceration. The dependent variable—dichotomized for the first research  question and used as a count variable for the research  second question—was asked of respondents in NSYR Wave 4. The survey item is: “How many times have you ever spent time in a jail, prison, juvenile detention center or other correctional facility?” The response categories range from “11 or more times” (coded as “1” in the NSYR Wave 4 data) to “Never” (coded as “12” in the NSYR Wave 4 data). I reverse coded this variable for Research Question 2 and dichotomized the reverse coded variable (“never” = 0) for Research Question 1.  The first operationalization will allow me to analyze patterns in odds of incarceration or having spent time in some type of correctional facility. The second analysis will allow me to analyze recidivism in NSYR Wave 4 respondents. Recidivism in youth and young adults typically involves crimes with shorter sentencing—as it would be nearly impossible for youth and young adults with sentences upward of ten years to be incarcerated

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again after such a long period of time given the timeframe of the NSYR Wave 4. Nonetheless, looking at predictors of the number of times incarcerated provides insight into recidivism concerning crimes with shorter sentences. Independent Variable: Type II Model-Based Learning Type II MBL “involves accumulating information about the decision environment and using that information to build a causal model of that environment… [which] corresponds to what we would naturally identify as reasoning and planning: using an understanding of how the world works to identify a sequence of actions that will get one to one’s goal” (Greene 2017: 69; see also Cushman 2013: 227). This means that MBL requires three interrelated elements. It (1) uses a causal model (or “understanding of how the world works”) (2) to select actions (3) to achieve a goal. To proceed, then, I characterize forced-choice self-report survey data that indicates MBL in two ways that are consistent with the definition provided by neuroscience: (1) types of causal models used to select actions for goal pursuit—or “types of MBL” and (2) degree of to which the use of a given causal model shapes decision-making—or “degree of MBL use.” First, with “types of MBL,” we can identify whether the presence of a particular goal and corresponding causal model in a respondent’s decision-­ making predicts a given outcome. Second, “degree of MBL use” would isolate how the extent to which—or frequency that—individual use of a causal model to reason about the pursuit of a goal predicts a given outcome. This second type of variable should be based on survey items that ask how frequently a respondent uses a goal and causal model, or how important the use of that goal and causal model is for the respondent’s decisionmaking. While there are no variables in Wave 1 of the NSYR that qualify as a “degree” of Type II MBL, there is a survey item that provides data that can be used to create variables that qualify as “types”: the “How Decide” item, which has been used to create Type I “moral schema” variables (Vaisey 2009; Vaisey and Lizardo 2010; Hoffmann 2014). The NSYR “moral schema” variables (e.g., Vaisey 2009; Vaisey and Lizardo 2010; Hoffmann 2014) are derived from a survey item based on Bellah et al.’s (1985) qualitative findings on moral logics. The item is as follows: “If you were unsure of what was right or wrong in a particular situation, how would you decide what to do? Would you MOST likely 1. Do what would make you feel happy 2. Do what would help you to get

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ahead 3. Follow the advice of a parent or teacher, or other adult you respect 4. Do what you think God or the scripture tells you is right.” Constructed by Vaisey, each one of these items corresponds to a moral logic from Bellah et al.’s (1985) findings and are labeled as follows (respectively): expressive individualist, utilitarian individualist, community centered (or “relational” in Vaisey’s analyses), and theistic (Vaisey 2009). To proceed with the operationalization, we must understand the type of memory that corresponds with Type I and Type II cognition, respectively. There are two primary types of memory: nondeclarative (Type I cognition) and declarative (Type II cognition). According to neuroscience, “Nondeclarative memory is neither true nor false. It is dispositional and is expressed through performance rather than recollection. Here arise the dispositions, habits, and preferences that are inaccessible to conscious recollection but that nevertheless are shaped by past events, influence our behavior and mental life, and are an important part of who we are” (Squire and Wixted 2011: 267). Nondeclarative memory stands in contrast to the other major category of memory—declarative—which “allows remembered material to be compared and contrasted. The stored representations are flexible, accessible to awareness, and can guide performance in a variety of contexts” (Squire and Wixted 2011: 267). Thus, given these definitions of memory, we can see that responses about moral decision-making strategies would rely on declarative memory. Therefore, to “compare and contrast” (Squire and Wixted 2011: 267) what one usually does versus what one would do if one were unsure how to act is characteristic of declarative memory. Conversely, to measure habits or practice, we should follow the lead of cognitive science and use measures that report the frequency of behavior (Wood and Runger 2016: 296; Faust et al. 2018). Based on my review and application of findings from cognitive science and neuroscience, I argue that the NSYR data from Vaisey’s (2009) “schema”  survey item qualify as Type II MBL cognition. To interpret these schema data using tools and findings from cognitive science, I apply an empirically based typology of “social perceptual processes” outlined by neuroscientists from the National Institute of Health. This typology (Forbes and Grafman 2010) allows us to classify types of social perception and identifies three types of cognitive processes: “implicit” (also labeled “automatic processing” by the authors [ibid.: 301]), “explicit” (also labeled “controlled processing” by the authors [ibid.]), or “both” “implicit” and “explicit” processing.

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Of the classified “social perceptual processes” in the typology (ibid.: 315–16), Vaisey’s (2009) “moral schemas” survey item can be classified as eliciting reports of “strategies in novel contexts”—a term used by Forbes and Grafman (2010) to refer to social perceptual processes that draw upon “information processing components” that are “involved in predicting behavior in novel context and planning and action” (ibid.: 316). After reviewing the relevant research on “strategies in novel contexts,” Forbes and Grafman conclude that these “strategies” primarily draw upon explicit cognitive processing (for a summary, see Forbes and Grafman 2010: 311, 316)  and therefore declarative memory. These NSYR “moral schema” data qualify as indicating decision-making in a “novel context” because the survey question asks respondents about what they would do if they were “unsure of what was right or wrong in a particular situation.” Since the findings from neuroscience suggest that these NSYR schema data indicate “explicit” processes, we can investigate the extent to which they align with the definition of DPMO Type II MBL cognition. Recall that Type II MBL requires three interrelated elements. It (1) uses a causal model (or “understanding of how the world works”) (2) to select actions (3) to achieve a goal (Greene, 2017: 69; Cushman 2013). These NSYR schema data fit the second requirement of MBL as they asked respondents how they would select actions—or “how” they “would…decide what to do” if they were deciding what was moral. This survey item then presents respondents with an “expected outcome” of a moral judgment or behavior. The superordinate goal would be to make a moral judgment or behave morally. The subordinate goal is the specific strategy that the respondent would select to achieve the superordinate goal. Next, these data correspond to the first criterion of MBL as the item prompted respondents to reveal their “causal model” for understanding moral actions by selecting a strategy for how they would “decide.” The options were: “1. Do what would make you feel happy [Expressive] 2. Do what would help you to get ahead [Utilitarian] 3. Follow the advice of a parent or teacher, or other adult you respect [Relational] 4. Do what you think God or the scripture tells you is right [Theistic].” It would be impossible to select a response, such as “what would make you feel happy,” if the respondent did not have a causal model for understanding which actions made them “feel happy.” The third response—following the advice of a respected adult—is a bit more complex, because it involves two subordinate goals: one that directs the respondent to a respected adult for understanding morality, and one that is provided in the form of the respected adult’s advice.

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For the “Relational” category, or “[following] the advice of a parent or teacher, or other adult you respect,” one might argue that this involves “Other Processing” (Forbes and Grafman 2010: 315). However, for  “other processing” to “account for ambiguous behaviors” (ibid.), it  draws upon explicit processing (ibid.: 312). This is also distinct from “social mimicry,” which draws upon implicit processes (Forbes and Grafman 2010: 315) because this involves “predicting behavior” rather than observing another’s actions in a situation and replicating these actions (ibid.: 315–6). The other three responses do use “well-learned beliefs toward others” but are not implicit because they do not involve “normal courses of behavior in general” (ibid.: 315), but instead, involve predicting behavior in a novel context—or “particular situation”—in which the respondent was “unsure of what was right or wrong” (NSYR Wave 1). This predictive element, as well as the degree of ambiguity concerning the action, makes these responses classifiable as “strategies in novel contexts” (Forbes and Grafman 2010: 316). Finally, these data correspond to the third MBL criterion, because the respondent’s superordinate goal—moral behavior or judgment—is implied by the question of figuring out what to do in the specific instance where the respondent was not sure what was “right or wrong.” Furthermore, using the goals and habits literature from cognitive science (Wood and Runger 2016), the “utilitarian” and “expressive” responses can be interpreted as “goals,” and using the DPMO model we can classify these as subordinate goals (see Chap. 5 for more on goal types in the DPMO). This is because “goals energize and direct action by defining a desired end state” (ibid.: 291). The wording of the schema survey item specifies an end state for these two options—being “happy” for the “expressive” schema and getting “ahead” for the “utilitarian” schema. Therefore, taken together, it appears that definitions and findings from psychology and neuroscience support an interpretation of these NSYR schema data as DPMO Type II MBL cognition. Following established operationalization practices with this survey item (Vaisey 2009; Vaisey and Lizardo 2010; Hoffmann 2014), I dichotomized each response to create separate variables. This resulted in my creation of four variables: “expressive,” “utilitarian,” “relational,” and “theistic.” In line with Vaisey’s (2009) use of these data to predict deviant behavior, I used the “Theistic” variable as a reference category.

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Independent Variable: Type I “Model-Free Reinforcement Learning” To review, the DPMO Type I cognition—or “Model-Free Reinforcement Learning” (MFRL)—is based on experiential learning and automatically attributes positive or negative values to stimuli based on prior outcomes. MFRL then generates automatic responses to current stimuli and expected outcomes given its conditioning. The resulting automatic responses can often divert the respondent from achieving the superordinate goal— thereby failing to produce the expected outcome (Cushman 2013; Greene 2017). Recall that in Chap. 5, I established that Type I MFRL used similar cognitive processes as Vaisey’s (2009) “practical consciousness.” This means that to operationalize Type I MFRL, we must then find measures for the type of memory that Type I MFRL employs. Work in neuroscience establishes that Type I MFRL develops habitual responses (Greene 2017). Furthermore, work on the psychology of habit establishes that habits rely upon procedural memory (Wood et  al. 2021). Thus, to operationalize Type I MFRL for the Sociological Dual-Process Model of Outcomes, we must operationalize moral habits. Doing so will allow me to build sociological tools for operationalizing this cognitive process using very specific types of forced-choice self-report survey data from the NSYR. There is an entire literature in cognitive science and neuroscience devoted to studying how procedural memory generates habitual “evaluation and judgment.” Recall that in neuroscience “procedural knowledge referred primarily to skill-based information, where what has been learned is embedded in acquired procedures” (Squire and Wixted 2011: 266). Furthermore, habits are automatic responses to reoccurring stimuli—or cues—that occur despite individual short-term goals or instances of adverse outcomes for a previous instance of habitual behavior (Wood and Runger 2016). In the cognitive science literature, procedural memory-based habit is measured using “probabilistic classification learning tasks” (e.g., Knowlton et al. 1996; Poldrack et al. 2001; Schwabe and Wolf 2012). In laymen’s terms, this means that psychologists measured how well participants learned patterns that were generated probabilistically by computer programs—and demonstrated this learning through motor response (such as pressing a button). The typical experiment unfolded in the following manner: First, the respondent was presented with a stimulus—most often a series of shapes or symbols. Next, (s)he was asked to make a prediction

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based on that stimulus using a prompt provided by the researchers on a computer program (i.e., does this series of shapes mean that it will rain or be sunny?). The outcome would be determined probabilistically by a computer program—meaning that a pattern of shapes or symbols would not always be correlated with an outcome (rainy or sunny), but would be weighted toward an outcome. The respondent would then be prompted to make a prediction based on the presented stimulus, would communicate that prediction through some physical action—such as pressing a button,  and would subsequently be told whether (s)he was correct or not. The stimulus would be presented a set number of times, and the accuracy of the participant’s guesses would provide data on the degree to which (s) he had learned the probabilistically generated pattern. This experimental design draws upon the “stimulus-response model” and measures how well respondents learn physical responses (pressing the right button) based on weighted repetition of outcomes linked to neutral stimuli. This model has evolved and has been utilized in various iterations, but typically employs the same sort of underlying design logic to link correlation between stimuli and outcome to a respondent’s generation of a motor response (e.g., pressing the right button). Thus, these experiments provide evidence of automatic processes of evaluation and judgment developed by respondents through conditioning that generate motor responses—or habitual evaluation and behavior generation activated in procedural memory. In this model, habitual evaluation, judgment, and behavioral response are inferred by a statistically significant connection between outcome weighting and correct motor response. Further research, including studies that employ fMRI, has found that this type of learning triggers activity in areas of the brain that are involved in motor control (for a review, see Balleine et al. 2007)—further supporting the classification of these motor-­ based skill dispositions as procedural memory. Subsequently, one study established that in an experimental context, if a respondent repeats—12 or more times—a manual task that links a stimulus to an outcome that is desired by the respondent, then the respondent develops an automatic motor response to that stimulus—even when the respondent has reached satiation with the once desired outcome. To explain further, researchers (Tricomi et al. 2009) gave respondents the opportunity to press a button every time a stimulus appeared—in this experiment, once every ten seconds—that rewarded them with either chips or candy (according to the respondent’s preference). After a series of

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trainings, the respondents were given chips or candy until they were satiated. Respondents were then once again presented with the stimulus and opportunity to press the button to be rewarded with their previously desired outcome. These respondents, despite having reached satiation, still automatically responded by pressing the chips or candy button. Respondents were monitored with fMRI during this final phase of the experiment. The fMRI findings revealed that this automatic response process corresponded with activation in regions of the brain associated with motor skill acquisition (Tricomi et al. 2009). Taken together, these findings suggest that— despite the original goal for respondent stimulus-­ response—once an individual performs a motor response enough times, (s)he develops procedural memory of the stimulus-response process—which then automatically generates the habitual response to the given stimulus. It is important, then, to find indicators in self-report survey data that connect repeated stimuli to repeated motor action, which would then serve as indicators of moral or immoral habits activated in procedural memory. To do so, I used literature in cognitive science to both define and understand how to measure a “habit.” Wood and Runger (2016: 292) summarize the cognitive science literature on habits by explaining that habits are automatically generated to the extent that there is “(a) activation by recurring context cues and (b) insensitivity to short-term changes in goals (a.k.a., not goal dependent), including changes in the value of response outcomes and the response-outcome contingency” (Wood and Runger 2016: 292; e.g., see also Tricomi et al. 2009). In other words, habits are automatic responses to reoccurring stimuli—or cues—that occur despite individual short-term goals or instances of adverse outcomes for a previous instance of habitual behavior. This reaffirms theories of culture and cognition from sociology about the importance of understanding interaction in terms of actors’ responses to cues (Martin 2010). Following the self-report habit literature—and given the available data in Wave 1 of the NSYR—I use self-reported frequency of social behavior. Second, a key feature of procedural memory is that it occurs “regularly” in response to given stimuli (or “cues”). Thus, my operational definition of MFRL Type I, given these data, is self-reported behavior that occurs “regularly” in response to a set of environmental cues. This conceptualization and usage of language concerning practical consciousness developing out of “regular” behavior appears in both Bourdieu’s conception of “habitus” and the habit literature  in psychology (e.g., Bourdieu 1990; Wood and Runger 2016).

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Furthermore, my operationalization builds on work in the psychology of habit in which habits are regularly measured by psychologists with forced-choice self-report survey data on activity “frequency” (Wood and Runger 2016: 296; Galla and Duckworth 2015; Faust et al. 2018). Finally, it is important to note that while all cognitive processes involved in habits cannot be dichotomized as a Type I process (Wood 2017; Hagger 2020), there is an automatic element of habit based on repeated activity that uses procedural memory (Wood et al. 2021) and is primarily employed by Type I MFRL (Greene 2017). Given my identification of “habit activated in procedural memory” as the cognitive process to which MFRL/practical consciousness is referring, what type of self-report NSYR Wave 1 data should we select and how can we operationalize them as variables that are relevant to the outcome of respondent incarceration reported in Wave 4? Concerning the type of data, it is worth repeating that habits are regularly measured by psychologists with forced-choice  self-report survey data on activity “frequency” (for a review, see Wood and Runger 2016: 296; also Galla and Duckworth 2015). The frequency of this activity can then be measured in both “relative” and “absolute” terms. It is important to note that some scholars of the psychology of habit judge “relative” measures of frequencies to be “suboptimal” for the operationalization of habit (Gardner et al. 2014). Following the self-report habit literature—and given the available data in Wave 1 of the NSYR—I use self-reported frequency of social behavior involving motor activity related to moral behavior. Second, a key feature of habits—as defined in cognitive science—is that they are behaviors that occur “regularly” in response to given stimuli (or “cues”). Thus, my operational definition of “habit activation in procedural memory”—given these data—is self-reported behavior that occurs “regularly” in response to a set of environmental cues. This conceptualization and usage of language concerning practical consciousness developing out of “regular” behavior is a key feature of the psychological definition of “habits” (Wood and Runger 2016). I operationalized MFRL variables by dichotomizing respondent reports of behavioral frequency. The two categories are “0”= not likely to be MFRL, and “1”= likely to be MFRL-driven behavior. Furthermore, I selected survey items that asked participants to report behaviors that occurred in response to an environmental cue. Thus, I selected survey items that either (a) presented participants with an environmental cue—or set of cues—and then asked them how they responded or (b) asked about behavior that required the presence of a cue to perform the behavior.

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An example of the first type of survey item is “how often the respondent cheated on homework or an exam.” This type of question qualifies because it specifically asks participants about how they responded—by cheating—to cues: exams and homework. An example of the second question is substance use. While this type of question directly asks about how frequently a respondent used a substance, this usage is a response to the availability of the substance to the respondent. Next, we must code frequency responses in terms of regularity or repetition. As defined in the habit literature in cognitive science, “habits are likely to form from responses repeated contiguously with context cues” (Wood and Runger 2016: 295, for an additional review, see Galla and Duckworth 2015; Wood et  al. 2021). These definitions fit the Type I MFRL requirements of occurring through reinforced experience. Scholars have operationalized habit strength in terms of scores on a forced-­ choice self-report based habit index (Galla and Duckworth 2015; Neal, Wood, and Drolet 2013), but have yet to operationalize a cutoff point for an approximation of the presence or absence of habits for forced-­ choice self-report survey data. While researchers seek to add more tools for measuring habits, the forced-choice  self-reported behavior frequency index  remains a central tool for habit researchers who seek to utilize survey data (Wood 2017). Behavior frequency has also been established as an empirical indicator of the automatic “triggering” of the habitual “selection” and “initiation” of action (Gardner et al. 2016). Thus, I use available resources from cognitive science to create my operationalizations of MFRL using forced-choice self-report survey data. Ultimately, I made use of two different types of behavior frequency data: relative and absolute (Gardner et al. 2014). In order to extend this model to incarceration outcomes, I began by assessing all seven of Vaisey’s (2009) prosocial or deviant social “action” variables (Vaisey 2009: 1705): underage drinking, marijuana usage, cutting class, cheating on school work, keeping secrets, volunteering, and helping others. These behaviors “typically involve social interaction” (Vaisey 2009: 1705) and, I argue, corresponding patterns of motor activity. Six out of these seven variables are responses regarding behavior frequency in response to a cue. The only one of these survey items that I could not use for an MFRL operationalization because it did not measure behavior frequency in response to a cue asked respondents: “In the last year, how often, if ever, did you do things that you hoped your [PARENT TYPE] would never find out about.” This question does not correspond to a specific behavior,

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or type of behavior—as the motives for teenagers wanting to keep secrets from their parents vary widely, or present a specific cue, but instead corresponds to an adverse outcome. However, the question indicates potential deviant behavior, thus justifying its inclusion in the analysis without MFRL Type I coding. Furthermore, I did not use the “volunteering” survey item because item Y120 of NSYR Wave 1 establishes that many respondents volunteered in lieu of juvenile incarceration, and NSYR Wave 1 never differentiated between reasons for volunteering. Furthermore, I dropped the “cutting class” survey item because it excluded respondents who were homeschooled. This left four survey items from Vaisey’s (2009) original prosocial and deviant behavior survey items that I could develop use MFRL measures. Drawing upon the work of scholars on religion and deviance, I also included “frequency of religious service attendance” as a variable of interest (e.g., Hoffmann 2014)—notably because it involves a discrete chain of motor behaviors that are a response to an environmental cue (presence of respective religious organization). There was also an item that asked respondents how frequently they prayed “by yourself alone.” I did not include this as a practice variable because it did not include a clear environmental cue. Several items asked respondents about behaviors that were responses to environmental cues. For example, a question about prosocial behavior asked “In the last year, how much, if at all, did you help homeless people, needy neighbors, family friends, or other people in need, directly, not through an organization?” Presumably, then, the cue would be the stimulus of the presence or awareness of those in need (which requires the respondent to interpret these potential recipients of aid as being “in need”). The response, then, would be the frequency in which the respondent “directly” helped those “in need.” Therefore, the deviant behavior variables that I used were “underage drinking,” “marijuana usage,” and “cheating on school work.” The prosocial behavior I used was “helping others.” Finally, the religious practice variable I used was “frequency of religious service attendance.” An item that used absolute terms for behavioral frequency was “drinking.” The “drinking” item asked respondents “How often, if at all, do you drink alcohol, such as beer, wine or mixed drinks, not including at religious services?” This item is then expected to ask about underage drinking and gives the respondents the following choices: “1. Almost every day 2. A few times a week 3. About once a week 4. A few times a month 5. About

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once a month 6. A few times a year 7. Never.” I propose coding those who estimated that they drank “About once a month” or more frequently as “habit.” “Regularly” implies a degree of predictability and frequency relative to everyday behavior. The cutoff, I argue, is a behavior that occurs predictably (“about once a month” as opposed to “a few times a year”) to a degree that the respondent could feasibly have engaged in this practice enough times to develop a habit. When using data with relative frequency, I selected options that indicated “regular” behavior as operationalizations of habit. For marijuana use, for example, respondents were asked “How often, if ever, have you used marijuana? Was it: 1. Never 2. You tried it once or twice 3. You use it occasionally, or 4. You use it regularly.” Here I would only code “use it regularly” as a likely indicator of habit. Once again, I used predictability and an implied degree of high frequency to code for likely indicators of “habit.” This means that I would code “sometimes” or less frequently as “0.” I coded “very often” and “fairly often” as “1,” given that “often” implies a relatively high degree of frequency and a degree of predictability. I recognize that these coding schemes could be susceptible to availability bias (e.g., Tourangeau, Rips, and Rasinski 2000)—however, this type of bias weights estimations toward more frequent experience. While no bias is desirable, a potential skew in the data toward those who had more frequent or regular behavior near the time of the survey could serve to include those with newly formed habits and exclude those whose habitual behavior has fallen out of practice. Independent Variable: Type II Integrative Processes/Deliberation Between Competing MBL and MFRL Inputs In the DPMO from neuroscience, Type I MFRL and Type II MBL processes are brought together in a subsequent step of Type II individual-­ level “deliberative processes,” which are defined as “[cognitive] processes [that] are flexible and integrative in the sense that they involve a conscious and controlled consideration of multiple inputs… [although] some of these inputs are ‘fast,’ inflexible, and often decisive” (Greene 2017: 68; Cushman 2013). For the sake of this analysis, we can measure whether a variable that indicates integration of Type I and II processes has a significant predictive association with incarceration.

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To create a variable for Type II Integrative Processes, I selected the following survey item: “How important or unimportant is religious faith in shaping your major life decisions?” Respondents had the following options for selecting degrees of importance “1. Extremely Important 2. Very 3. Somewhat 4. Not very, or 5. Not important at all.” To begin, I selected a variable that indicated the “degree” of importance that an individual perceived a type of Type II MBL cognition had on their perceived decision-making process. This item captured the “degree” element of Type II cognition because it asked respondents to assess the level of importance of this type of reasoning for their perceived decision-­ making process. Second, this qualified as Type II MBL cognition because reasoning using “religious faith” satisfies all three of the criteria for Type II MBL. Regarding the first and third requirements that I outlined for operationalizing Type II MBL, religious faith provides an understanding of how the world works based on a causal religious ontology for actions that help the believer achieve “salvation” (Durkheim, 1995 [1915]: 419). Finally, the data generated from this item pertain to the “selection of actions” via moral judgments  in that the question concerns the importance of faith in “shaping” “major life decisions.” However, faith also relies heavily on intuition and “embodied knowledge” (Ignatow 2007; Stoltz and Lizardo 2018)—qualifying it as Type I MFRL cognition. Finally, since the question asks if respondents are aware of how faith shapes their decisions, this process would be a “conscious…consideration” of the effects of religious faith on their decisions— qualifying this as a form of deliberation that integrates Type I MFRL and Type II MBL cognition. Therefore, this survey item is appropriate to use as the Type II Integrative Processes variable because it fits my criteria for Type I MFRL, Type II MBL, and their subsequent Type II integration. This variable is also based on the literature on faith as the interaction between Type I and Type II processes (Winchester 2016). Control Variables I used replicated control variables from studies that used the NSYR to study the relationship between schema and deviance (Vaisey 2009; Hoffmann 2014). For a summary of these variables and my replication using instructions from Vaisey (2009) and Hoffmann (2014), see Appendix A.  For the summary statistics of the entire analysis, see Appendix B.

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The control variables from these studies are largely consistent with those from other studies that use the NSYR to study the relationship between religiosity and deviance (Longest and Vaisey 2008; Rivera et al. 2018). I then supplemented my analysis with control variables I found for deviance from the youth delinquency literature: mental health, youth status, and neighborhood safety (e.g., Haynie et  al. 2014: 698–9; Haynie and South 2005). Other standard control variables for youth delinquency—such as youth vocabulary, parental occupation, or parental receipt of public aid—were not available in the NSYR Wave 1 data set. For cognition controls, I included a measure of “moral schema” from Hoffmann’s (2014) study. This variable is based on the following item: “‘Do you yourself sometimes feel confused about what is right and wrong, or do you usually have a good idea of what is right and wrong in most situations?’ (0 = feel confused; 1 = something in the middle; 2 = have a good idea)” (Hoffmann 2014: 189). This variable was not constructed using findings from cognitive science and does not fit the definition of a type of cognition used in the dual-process model of outcomes, so I treated it as a control variable. Furthermore, Victor, Miles, and Vaisey (2015: 786) constructed a variable for “moral worldview.” I considered including this variable, which could be a proxy for Weber’s theory that “world images…have determined” (Weber 1958 [1913]: 280) how “material and ideal interests” are interpreted and pursued. However, to use this item to approximate Weber's conception of the “switchman,” this construct we would also need a corresponding measure of interests that were being interpreted through this worldview, and such a measure does not exist in the NSYR Wave 1 data. Furthermore, as a control, this variable—which asks about respondent moral positions—excludes a great deal of cases. In the final Wave 4 analysis with weights, this one variable alone reduced the sample size from 1564 to 1437. This is due to the high amount of “don’t know” responses. This measure, as constructed, also excludes atheists. Thus, I did not include it in my analyses. Interaction Effects, Mediation, and Moderation I did not include analysis of statistical interaction, mediation, or moderation due to the scope of this analysis. I intend to provide initial evidence of empirical associations between cognitive processes learned through  cultural socialization that likely drive moral judgment on the one hand and the

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outcomes of moral judgment on the other. As such, this analysis only aims to demonstrate the predictive effects of these DPM outcome cognition variables. If successful, these findings should be used as a springboard for investigations into relevant statistical interaction, mediation, or moderation.

Analysis Analytic Strategy Analyses utilizing the dual-process model of outcomes face an important conundrum that complicates empirical investigation: these analyses must use longitudinal data that track the effects of actors at an initial time period on an outcome in a subsequent time period. This means that the dependent variable appropriate for a DPMO often—by nature of the process— does not exist in the initial survey wave or period of observation. Taking this into account, it would be inappropriate to analyze these data using standard techniques for longitudinal analysis. For example, fixed-effect analysis requires the dependent variable to be “measured for each individual on at least two occasions” (Allison 2009)—which does not apply to my analysis. We find a similar structure for voting data when data from a pre-­election wave is used to measure effects on the respondent’s post-election report of vote choice. For these analyses, scholars use standard regression techniques. For binary vote choice, researchers utilize logistic regression (e.g., McVeigh and Diaz Maria-Elena 2009; Jacoby 2010), while for voting choices that involve multiple candidates, analysts use techniques such as multinomial logistic regression (e.g., Marx 2016). Similarly, McVeigh et al. (2014) utilized logistic regressions to investigate the effects of individual and county-level factors from earlier time periods on both the probability of the county-level presence of Ku Klux Klan organizations and the probability of individual intent to vote Republican in later time periods. Scholars also use logistic regression to measure the presence or absence of health risk factors (Hill et al. 2017; Silver et al. 2020). Furthermore, scholars regularly use negative binomial regression when analyzing count variables, such as Srivastava and Banaji (2011)—who measure the effects of implicit (and explicit) self-assessment on the number of network ties for collaboration across different organizational factors. Another example comes from Almeida (2012), who analyzes the effects of state infrastructure on the number of protests against liberalization in El Salvador and Costa Rica.

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Thus, for my binary operationalization of the Wave 4 outcome variable, I used logistic regression. Furthermore, for the count variable operationalization of my outcome, I used negative binomial regression. Finally, I employed negative binomial regression for the latter analysis based on over-dispersion tests I performed for all four count variable models (for a discussion, see Almeida 2012: 1062). Results: Logistic Regression For the relevant results, I refer to Models 2 through 4 in Table 6.1. In Model 2, I added Vaisey’s (e.g., 2009; Vaisey and Lizardo 2010) and Hoffmann’s (2014) moral schema variables to an initial analysis using only control variables. In this model, we can see that the “Relational” Type II cognition/schema variable—in which respondents said they would seek advice from adults they respected to address ambiguous moral situations— was significantly associated with higher odds of the respondent having spent time in a correctional facility than those who used the “Theistic” Type II cognition/schema—or estimated that they would resolve such moral conundrums by doing what “God or Scripture says is right.” In Model 3, I introduced relevant behavioral variables operationalized using the aforementioned Type I MFRL coding. This coding revealed that the practice of regularly attending religious services served to statistically significantly reduce the odds of the respondent having spent time in a correctional facility at least once. Model 4 included Type II/schema variables, Type I MFRL coding, and the Type II Integrative Processes variable. This means that holding all other variables in the model constant, respondents who habitually attended religious services had 42% lower odds of being incarcerated at least once as compared with those who did not habitually attend religious services. Furthermore, the “Relational” Type II/schema variable remained statistically significantly associated with higher odds of being incarcerated at least once. Additionally, in this model the “Utilitarian” Type II cognition/schema variable—in which respondents estimated that they would do what would “help” them “get ahead” to resolve morally ambiguous situations—became statistically significantly associated with higher odds of the respondent having spent time in a correctional facility at least once as compared to those who responded with the “Theistic” Type II cognition/schema. Finally, the variable for the integration of Types I and II cognition was not significant in this analysis.

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Table 6.1  Logistic Regression: Odds Ratios for Wave 4 Reports of Respondent Incarceration (or having spent time in some type of correctional facility) At Least Once versus Not Incarcerated (or having spent time in some type of correctional facility) At All Model 1 (Socioeconomic, Network, and Deviance Controls)

Schema (Type II MBL and Control)d Vaisey Schema: – Expressive (Type II MBL) Vaisey Schema: – Utilitarian (Type II MBL) Vaisey Schema: – Relational (Type II MBL) Hoffmann – Schema: Confused about morality (Control variable) Type I MFRL Coding Type I MFRL – Coding: Marijuana Type I MFRL – Coding: Drink Type I MFRL – Coding: Cheated Type I MFRL – Coding: Helped Type I MFRL – Coding: Attend Religious Services Type II Integrative Processes Effects of faith of – major life decisions

Model 2 (Add Moral Schema Variables—Type II MBL and Control Variables)

Model 3 (Add Type I MFRL Coding)

Model 4 (Type II MBL Schema Variables, Type I MFRL Coded Variables, and Type II Integrative Processes)

1.70

–

1.87

1.81

–

2.17a

1.87a

–

1.94a

0.93

–

0.93

–

2.99a

3.06a

–

2.56c

2.48c

–

1.06

1.11

–

0.97

0.99

–

0.58a

0.58a

–

–

1.26

(continued)

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Table 6.1 (continued) Model 1 (Socioeconomic, Network, and Deviance Controls)

Model 2 (Add Moral Schema Variables—Type II MBL and Control Variables)

Network Characteristics Number of 1.00 1.04 Friends Proportion use 0.85 0.88 drugs Proportion get in 1.95 2.04 trouble Proportion similar 0.65 0.66 Beliefs Proportion same 1.38 1.41 religious group Proportion 0.72 0.72 religious Adult Network 0.92 0.98 Closure Religious Involvement and Religiosity Measurese Attend Religious 0.93 0.93 Services Evangelical 4.19c 4.07c Mainline 4.70c 4.47c African American 4.32b 4.44b Protestant Catholic 1.94 1.83 Jewish 1.01 1.01 Mormon 2.54 2.53 Religion: Other 2.38 2.44 Religion: Don’t 5.47b 5.22b Know Religious Salience 1.04 1.06 Feels Close to 0.99 1.00 God Prayer 1.05 1.06 Parental Factors Family Cohesion 0.95 0.95

Model 3 (Add Type I MFRL Coding)

Model 4 (Type II MBL Schema Variables, Type I MFRL Coded Variables, and Type II Integrative Processes)

1.01

1.05

1.18

1.19

2.24

2.37

0.65

0.64

1.40

1.49

0.67

0.70

0.97

1.04

–

–

4.47c 4.97c 4.64b

4.47c 4.72c 4.87b

2.02 0.89 2.61 2.58 5.83b

1.89 0.84 2.67 2.59 5.67b

1.05 1.02

0.95 1.00

1.05

1.05

0.95

0.94 (continued)

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L. A. VILA-HENNINGER

Table 6.1 (continued) Model 1 (Socioeconomic, Network, and Deviance Controls)

Model 2 (Add Moral Schema Variables—Type II MBL and Control Variables)

Model 3 (Add Type I MFRL Coding)

Model 4 (Type II MBL Schema Variables, Type I MFRL Coded Variables, and Type II Integrative Processes)

0.99

0.98

0.98

0.87c

0.88c

0.87c

0.35c 0.88 1.69 1.64a 1.00 1.02

0.34c 0.91 1.64 1.69a 0.95 1.02

0.33c 0.90 1.50 1.61 0.93 1.02

0.89b 0.82

0.90b 0.73

0.89b 0.79

0.66c

0.64c

0.64c

1.51b 1.27b 1.08 0.98 1.05

– – – 1.03 –

– – – 1.00 –

1.05 0.84

1.05 0.84

1.05 0.86

1.22 0.54

1.22 1.60

1.25a 0.66

Parental 0.98 Monitoring Parental 0.87c Religiosity Demographicsf Female 0.35c Age 0.87 Race: Black 1.81 Race: Other 1.71a Region: South 0.99 Parental 1.02 Education Parental Income 0.89b Two-Parent 0.78 Family GPA 0.67c Deviant and Prosocial Behaviors Marijuana 1.51b Drink 1.30c Cheated 1.08 Secret 0.99 Helped 1.06 Deviance Variables Peer Status 1.05 Parent: How safe 0.83 is neighborhood Depression 1.21 Constant 1.10

All analyses were conducted with the NSYR Wave 4 Panel Weight