The structural basis of word association behavior 9783111352947, 9783110997859

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THE STRUCTURAL BASIS OF WORD ASSOCIATION BEHAVIOR

JANUA LINGUARUM STUDIA MEMORIAE N I C O L A I VAN W I J K D E D I C A T A edenda curat

C. H. VAN

SCHOONEVELD

INDIANA UNIVERSITY

SERIES

MINOR

NR. LI

1966

M O U T O N & CO. THE H A G U E • PARIS

THE STRUCTURAL BASIS OF

WORD ASSOCIATION BEHAVIOR by

HOWARD R. POLLIO University of Tennessee

1966

MOUTON & CO. THE HAGUE • PARIS

© Copyright 1966 by Mouton & Co., Publishers, The Hague, The Netherlands No part of this book may be translated or reproduced in any form, by print, photoprint, microfilm, or any other means, without written permission from the publishers.

Printed in The Netherlands

PREFACE

Words are impressive things. Philosophers, such as Susanne Langer, see in them the differentiation of man from beast. Semanticists, such as Hayakawa and Chase, view their effects with suspicion, feeling that modern man has not been able as yet to disentangle himself from the pernicious view that words have a life independent of the object signified. For the psychologist, however, no such sweeping hypotheses are possible. Words do not ennoble or tyrannize; rather they serve as the building blocks of language and must be considered simply as the elementary units of verbal behavior. Given this understanding, the problem of the psychologist with respect to words is to uncover the system of relations which exists among them and to describe the empirical consequences of this organization. In what way may words be related? Previous work suggests that they may be related in terms of their location on some specificable dimension or dimensions such as are provided by Osgood's semantic differential. They may also be related in terms of their position within a network of words, such as has been described by Deese in his analysis of the structure of associative meaning. In both cases, however, words must be considered simply as elements within a total cognitive organization. The present study seeks to understand the effects of words within this context and to suggest a specific hypothesis as to the nature and characteristics of a semantic structure which presumably provides the basis of adult association behavior. The early portions of the present work present a selective review of previous research concerned with describing the ways in which meaningful English words are related. This review focuses primarily on data gathered through the use of a variety of proce-

6

PREFACE

dures known generically as word association, or on data gathered through the use of rating procedures similar to the semantic differential. These results suggest the nature of a theoretical semantic organization which is capable of encompassing relations derived from both assessment procedures. This organization generates a number of easily verifiable predictions which are then put to an empirical test. Finally, the results of this experimental test are viewed in terms of their implications for other aspects of verbal behavior such as serial learning, multiple association and concept formation. This book owes its existence directly or indirectly to many hands. First of all, I would like to thank Arthur W. Melton, of the University of Michigan, who gave generously of his time and advice on all matters concerning this study and who directed the course of my graduate training. Helen Peak, also of the University of Michigan, gave generously of her knowledge in order to provide me with a strong feeling for psychological theory as well as for the intricacies of cognitive processes. Indeed, many of the concepts found in the present work owe their origin to problems discussed initially in her seminar in Cognitive Processes. The analyses and results presented in the present study were dependent in a large measure upon United States Public Health Research Funds provided to the author. The initial phases of this research were supported by a predoctoral research fellowship awarded while the author was at the University of Michigan, while subsequent sections were undertaken under the support of United States Public Health Grant MH-08903-1. These awards are gratefully and humbly acknowledged. I would also like to thank Helen Konapek who typed the preliminary draft of the present manuscript, as well as Charles Wing who helped design the apparatus and who drew up the final figures. Thanks are also due Olga Budor and Ann Disney who did much of the subsequent typing. Most of all, I would like to thank Marilyn Pollio who makes all things possible, and to whom this work is sincerely dedicated. HOWARD R . POLLIO

TABLE OF CONTENTS

Preface

5

List of Tables

9

List of Figures

10

I. Introduction: Conceptualization of a Semantic Structure

11

A. Inter-verbal Relations Among Words . . . 1. Associative Hierarchy Factors . . . . 2. Factors Affecting the Size of an Associative Hierarchy B. Words and Representational Mediation . . . C. Conceptualization of a Semantic Structure . . D. Semantic Structure and Associative Clusters . .

12 12 13 22 23 27

II. Semantic Structure and Continuous Word Association.

30

A. B. C.

Major Hypotheses Measurement of Semantic Distance . . . Measurement of Inter-Word Connectedness .

III. Experimental Test of Predictions A. Purpose B. Method 1. Subjects 2. Stimuli 3. Apparatus and Procedure

.

. .

30 31 32 . 4 0 40 40 40 40 41

8

TABLE OF CONTENTS

C.

Analysis of Results

48

1. Intra-Cluster Cohesiveness 2. Intra-Cluster Semantic Distances

.

53 57

.

66

IV. General Discussion and Conclusions

. .

.

. .

V. Summary

75

Appendixes: A. B. C. C.

Inter-Word Association Latency Distributions by Stimulus Word Individual Cumulative Association Curves by Stimulus Word 1. Evaluation of the Empirical Constants for Bousfield's Equation 2. Frequency Distribution of Sequence Size by Stimulus Word

77 79 88 88

Bibliography

89

Index

93

LIST OF TABLES

1. Stimulus Words and their Semantic Characteristics . . . . 2. Means and Standard Deviations of Relative Intra-Cluster Cohesiveness (MCR) as a Function of Sequence Speed and Stimulus Word 3. Analysis of Variance of the Differences among Transformed Mean Intra-Cluster MCR Proportions 4. Means and Standard Deviations for the MCR Values of 24 Randomly Selected Fast, Medium, and Slow Sequences 5. Analysis of Variance of the Differences among the Transformed MCR Values of 24 Randomly Selected Fast, Medium, and Slow Sequences 6. Means and Standard Deviations of the Intra-Cluster D Means as a Function of Sequence Speed and Stimulus Word 7. Analysis of Variance of the Differences in Mean Intra-Clusters B's 8. Means and Standard Deviations of the Intra-Cluster D Means of 24 Randomly Selected Fast, Medium, and Slow Sequences . . . 9. Analysis of Variance of the Differences among the Intra-Cluster D Means of Fast, Medium, and Slow Sequences

41 54 55 56 56 58 58 59 59

LIST OF FIGURES

1. Interrelationships among the First 3 Associates to the Initial Stimulus Word, MAN 2. Hypothesized Organization of a Semantic Structure . . . . 3. Hypothetical Arrangement of 3 Words in 2 Different Associative Clusters 4. Mean Cumulative Association Production as a Function of Association Time and Initial Stimulus Word 5. Mean Cumulative Association Rate for the Stimulus Word HOUSE 6. Mean Cumulative Association Rate for the Stimulus Word JUSTICE 7. Mean Cumulative Association Rate for the Stimulus Word THIEF 8. Mean Cumulative Association Rate for the Stimulus Word TROUBLE 9. Mean Semantic Distance for all Stimulus Words, between Successive Cluster Elements, with Evocation Speed as a Parameter . . . 10. Mean Semantic Distance between Successive Elements for Stimulus Word JUSTICE for Fast and Slow Associative Sequences . . . 11. Mean Semantic Distance between Successive Elements for Stimulus Word TROUBLE for Fast and Slow Associative Sequences . . . 12. Mean Semantic Distance between Successive Elements for Stimulus Word HOUSE for Fast and Slow Associative Sequences . . . 13. Mean Semantic Distance between Successive Elements for Stimulus Word THIEF for Fast and Slow Associative Sequences . . .

18 26 37 49 50 51 52 53 60 61 62 63 64

I INTRODUCTION: CONCEPTUALIZATION OF A SEMANTIC STRUCTURE

If a subject is instructed to respond with the first word that is suggested to him by a stimulus word he has little difficulty in complying with these instructions. Although the determiners of the associated verbal response have been described in terms of one or more of the classical laws of association, recent theory has focused attention primarily on one of two classes of events initiated by a stimulus word: hypothesized fractional conditioned meaning responses, and the specific words aroused as associates by the stimulus word. In the present paper, we will take the position that both classes of events imply, or at least suggest, certain relations among words and that these relations can be described by a single structural conceptualization encompassing both classes of events. It must be emphasized that these relations are inferred from the nature of the responses evoked in a subject by a stimulus word; the subject may or may not be aware of the existence of an underlying structure. The responses from which this structure may be inferred are conditioned meaning responses and overt word associations. In the sections which follow, we will examine interverbal relations among words; that is, relations inferred from results gathered through the use of any of a number of procedures known generically as word-association. In general, these procedures present S with a single stimulus word to which he is required to respond with either another single word, or with a number of other words suggested by the stimulus word. We will also examine semantic relations among words; that is, relations inferred from the independent rating of words which were elicited in some variety of the word association procedure. We will then attempt to show that it is possible to describe a single underlying organization of

12

INTRODUCTION

words which takes account of relations derived from considerations involving both classes of events; an organization based on conditioned meaning factors, and in which considerable importance is afforded to verbal clusters. This hypothesized structure generates a number of predictions, some of which can be tested through the relatively simple procedure of continuous word association. An experimental test of these predictions will then be described in detail.

A. INTER-VERBAL RELATIONS AMONG WORDS

1. Associative Hierarchy Factors From the earliest investigations of word association (Thumb & Mar be, 1901) it was known that any familiar stimulus word has a tendency to evoke the same associate from many Ss. By counting the relative frequency of occurrence of response words in a group of Ss, it is possible to order verbal associates in terms of their probability of emission as an associate to a specific stimulus word. Compilations of this sort (Kent-Rosanoff, 1910; Woodrow & Lowell, 1916; Russell & Jenkins, 1954; etc.) easily imply that word associates are ordered hierarchically; and make possible the further inference that a similar hierarchical arrangement describes the verbal response habits of an individual. Although this second assumption has long been made, only recently has any direct evidence become available (Rosen & Russell, 1957). The first type of relation implied by the word association procedure is a hierarchical one; that is, any given stimulus word serves consistently to arouse as associates, a collection of words which can be ordered in terms of their probability of evocation by the stimulus word. Early interest in the effects of different types of material on the rate of verbal learning led to considerations of the meaningfulness of the material employed. Characteristically, the meaningfulness of nonsense materials was defined by the number of Ss who "got an association" to that material in a brief time period. Here, as

13

INTRODUCTION

in the case of associations to meaningful material, the assumption was made that the percentage of 5"s getting an association to a nonsense syllable in a given time period mirrored the probability of an associate to that nonsense syllable by an individual S. The tenability of this assumption was strengthened by the positive correlation obtained between meaningfulness calibrated in this way, and ease of learning (McGeoch & Irion, 1952). Although many different investigators calibrated the meaningfulness of nonsense syllables through the association procedure described above (Glaze, 1928; Archer, 1960), it remained for Noble (1952) to extend the range of stimuli calibrated in this way to meaningful words. His Ss associated continuously to a stimulus word for one minute, and meaningfulness was defined as the mean number of verbal associations evoked by a stimulus word in the one minute interval. More pertinent to the present discussion, his results demonstrated that words consistently vary in the number of total associates available to them, i.e., words, considered as stimuli, can be ordered along a meaningfulness dimension. This in turn suggests that not only do words arouse a hierarchy of verbal associates but that this hierarchy varies in size for different stimulus words. 2. Factors Affecting the Size of an Associative

Hierarchy

The variables which significantly affect the size of an associative hierarchy have yet to be specified, although a number of suggestions have been either implicitly or explicitly made. Cofer and Shevitz (1952) have shown that the number of word associations produced in a 10 minute period is significantly affected by the frequency of occurrence of the stimulus word. Similarly, Underwood and Schulz (1960) have shown that the magnitude of the Noble m-value may be derived from the frequency of occurrence of the sequence of letters composing the stimulus word. In both cases the conclusion that more frequent words evoke larger hierarchies seems justified. The frequency of occurrence of the stimulus word is probably not the only factor determining the size of a verbal associative

14

INTRODUCTION

hierarchy. The frequency with which a stimulus word has been paired with other specific words, as well as the evaluative connotation of the stimulus word probably also affect the size of the associative hierarchy. Frequency of pairing should be reflected in the communality of the associated response, such that a word which has been paired frequently with a given stimulus word will tend to have a higher communality score as an associate to that word, than would be true for words which had been paired less frequently with that stimulus. If conditions of direct pairing affect the communality with which an associate is given, it should be possible to demonstrate a positive relationship between frequency of pairing and communality, or probability, of association. Osgood and Anderson (1957) provide evidence for this view. They showed that the probability of a given word being evoked as an associate in the word association procedure is in part a function of the number of times that the associated word had been previously paired with the stimulus word. The effect of frequency of co-occurrence, as reflected in a high communality associative relationship between two words, may be expected to affect the size of the associated hierarchy through Marbe's Law (Woodworth, 1938). Marbe's Law states that the communality of an associative response predicts the speed of that word's associative reaction time (also cf. Schlosberg & Heineman, 1950, as cited in Woodworth & Schlosberg, 1954, for a precise estimate of the relationship between communality and associative response latency). Although it thus seems probable that communality, conceptualized as frequency of co-occurrence, has some direct effect on the total number of available word associates (i.e., high communality precludes an extensive number of moderately strong associative verbal connections) the existence of this relationship has yet to be specified precisely. We have examined the revised Kent-Rosanoff norms (Russell & Jenkins, 1954) with this in mind, and have found, for the 100 words contained in this list, a reasonably linear relationship between the communality of a primary associate and the total number of associates evoked by a given stimulus word. A product moment correlation com-

INTRODUCTION

15

puted on these data yielded an r = -.57 {P < .01; N = 100). To some extent then, hierarchy size covaries negatively with the com munality of a stimulus word's primary associate.1 An extrapolation from the judgemental theory of emotion (as discussed in McGeoch & Irion, 1952) implies a positive relationship between evaluative connotation and hierarchy size. That is, words judged as pleasant should produce more associates than words judged as unpleasant. An earlier analysis by Noble (1958) did indicate that positive evaluation correlated significantly with m-value. A re-analysis of these data by Underwood and Schulz (1960) taking context factors into account failed to replicate this result. We have found, however, using words in the original Noble norms, a rank order correlation of .49 between the evaluative semantic differential rating (Jenkins, Russell & Suci, 1958) and the m-value of 19 words common to both lists. Although this correlation is not large relative to the number of cases, it becomes somewhat more significant when it is recalled that the stimulus words used by Noble were not selected for the extremeness of their evaluative connotation, and consequently, the range of their evaluative semantic differential ratings is quite restricted (1.80-4.40). Independent evidence supporting the hypothesis of a positive relationship between hierarchy size and positive evaluation is also to be found in a recent study (Koen, 1962) which revealed a marked correlation between the evaluative ratings of stimulus words and the number of associates produced by these words in a one minute time period. The relationship of frequency to hierarchy size has now been discussed in two cases. We have seen that frequent words tend to evoke larger hierarchies. We have also noted that the proba1

As a consequence of Marbe's Law, the time permitted for word association will probably affect the size of the obtained hierarchy. If, for example, 5s are permitted to associate for a relatively brief time period, words having high communality primary associates should produce more associates. If, however, the hierarchy is assessed for a longer time period, it is expected that this relationship will be reversed. Using Kent-Rosanoff norms as an estimate of total hierarchy size may be considered the equivalent of permitting a relatively long association period. Under this condition a significant negative correlation between these two variables is to be expected.

16

INTRODUCTION

bility that a given word will be given as an associate (as reflected by its communality score) is related to the frequency of previous co-occurrence of the stimulus and response words. Since, as we have previously noted, the mutual frequency of co-occurrence for two words creates a condition which precludes the establishment of a number of other moderately strong interverbal connections, it seems reasonable to propose that the means by which frequently occurring words come to evoke larger hierarchies is related to the frequency with which other words can occur continguously with them. Sheer availability makes possible more extensive pairing and consequently results in larger hierarchies for frequently occurring words. A word which occurs frequently in the language is also more likely to have an opportunity to become connected to a number of different words and consequently to occur frequently as an associative response. One prediction which arises from this hypothesis is that the probability of evocation of a given associate is directly related to the frequency of occurrence of that associate in the language. A closely related hypothesis has been employed by Underwood and Schulz (1960) in their attempt to specify the order in which response elements become available for connection in pairedassociate learning. Their discussion indicates that the order of availability of words, and by analogy, their order of emission as associates in the word association procedure, is determined by the frequency of occurrence of the associated word. They cite as evidence for this view the work of Cohen, Bousfield and Whitmarsh (1957), dealing with the hierarchy of words associated to a category name such as "furniture", "fish", etc.; as well as the work of both Johnson (1956) and Howes (1957), dealing with the relationship between frequency of occurrence of words in the language, and the frequency with which these words are emitted as word associates in the word association procedure. In the Johnson analysis (1956), for example, it was shown that of the associates to 10 Kent-Rosanoff stimulus words, the 10 most frequently given associates have Thorndike-Lorge (1944) frequencies greater than

INTRODUCTION

17

50 times per million in 84 % of the cases, whereas the comparable figure is 48 % for the least frequently given responses. These results indicate that the associative relationship between two words seems to depend in a large measure upon their frequency of cooccurrence. This frequency of co-occurrence, as we have already noted, is reflected in the ordering of elements in the obtained verbal hierarchy; an ordering which is strongly affected by the general frequency of occurrence of both words. The Phenomena of Associative

Clustering

Working with the hierarchy of words aroused by a stimulus word, Deese (1962) has been able to demonstrate the existence of clustering within the associative hierarchy aroused by a stimulus word. Beginning with the observation that each constituent element in a verbal hierarchy may itself be considered as a stimulus word, Deese is able to generate a matrix of verbal associations involving all of these associates. That is, a square matrix in which the row and column headings are the same words; words which originally were the associates to the stimulus word itself. The operations of factor analysis are then employed in order to uncover specific sub-clustering of verbal elements in the associative hierarchy of the initial stimulus word. This complex arrangement of words within an associative hierarchy has further implications for overt word association. When, for example, it is noted that the word TABLE overwhelmingly evokes the word CHAIR as its primary associate, it must also be remembered that TABLE evokes other words as associates, and, perhaps more significantly, CHAIR is often an associate to other words in the hierarchy aroused by the word TABLE. AS a consequence of Deese's analysis it is reasonable to diagram the nature of the relationships which exist among constituent elements in an associative hierarchy in terms of the extent and direction of their mutual evocation as associative responses. Figure 1 shows the relationship among three words aroused by the stimulus word MAN, and the word MAN itself. (These associations are found in the revised Kent-Rosanoff norms (Russell & Jenkins, 1954).)

18

INTRODUCTION

MAN

Woman 11

Boy

Girl

Fig. 1. Interrelationships among the First 3 Associates to the Initial Stimulus Word, MAN.

It is to be noted that in this particular example, rather than consider all of the verbal associations to the word MAN, for purposes of conveniences we have taken only the first three word associates to the word MAN, and the first three associates to each of these words. The arrows in the diagram indicate the direction of the association between the various words in this cluster. This method of diagrammatic representation has much in common with the technique of the sociogram in social psychology (Glanzer & Glaser, 1959), and as we will later demonstrate, many of the mathematical operations performed on the matrix of these relations, as well as some of the theoretical concepts assumed to underly these relations, are applicable to this type of data. Evidence for the behavioral effects of this type of associative structure on the recall of verbal elements is to be found in the earlier work of Deese (1959a, 1959b) and in the more recent work of Rothkopf and Coke (1961), and Pollio and Christy (1964). Attempting to predict specific verbal intrusions in immediate

INTRODUCTION

19

recall, Deese (1959a) has shown that the probability of a word being evoked as an intrusion in free recall is a linear function of the average frequency with which that word occurs as an associate to words in the training list. Rothkopf and Coke (1961), who were also interested in the fate of individual words in recall, demonstrated that the frequency of recall of individual elements in a partially learned list was strongly related to the extent that these elements were evoked as associates by other words in the same list. Along the same line of investigation, Pollio and Christy (1964) demonstrated that these inter-item associative tendencies are capable of producing not only facilitative effects on free recall but that under certain conditions, they may also actually interfere with free recall. Taken together, the results of these experiments serve to demonstrate, at the level of the associative hierarchy, that interrelationships within a collection of meaningful words exert a strong influence on the recall of specific items. It might be helpful at this point to review what we know about associative relations among words. We have seen that stimulus words consistently evoke a recurring collection of verbal associations. The size of this collection has been shown to vary as a function of a number of specifiable conditions. Elements within an associative hierarchy can be ordered in terms of their probability of evocation by the stimulus word. Relative frequency of both stimulus and response words, a factor which promotes frequent co-occurrence, was discussed as one way in which hierarchical organization is determined. Deese's analysis (1962) demonstrated that a stimulus word does not evoke a homogeneous hierarchy of elements, all more-or-less strongly connected to the stimulus word, but rather that associative hierarchies are organized into a number of substructures called clusters, each involving as strong, or stronger, within cluster word-association tendencies as between cluster word-association tendencies. The factors which determine order within the total hierarchy presumably also have an effect on these clusters. The phenomena of clustering in recall provides data consistent with this analysis. Given this system of interrelationships among words, it is pos-

20

INTRODUCTION

sible to assume that the position of each word within an associative hierarchy depends in some way upon the number of other elements in that hierarchy which evoke it as an associative response. In an attempt to provide some data for this conjecture, Pollio (1963a) has examined the intra-hierarchy structure of word associations given in response to the following 6 stimulus words: MUSIC, BUTTERFLY,

CHAIR, SLOW, COMMAND a n d

WHISTLE.

An

examination of these data indicated a positive relationship between hierarchy position and the number of other hierarchy elements eliciting a particular word as an associate in an independent assessment. Rank-order correlations varying in magnitude from .56 to .68 were found to obtain between these two variables when the number of intra-hierarchy associative evocations was summed across stimulus words by position. Further examination showed that the mean number of cues for words in the upper third of the associative hierarchy was significantly greater than comparable values obtained from the middle and lowest thirds of the hierarchies evoked by all 6 of the stimulus words. Thus, order of associative response emission depends to some degree upon the associative structure of the verbal hierarchy. The Phenomena of Continuous Word Association In much of the preceding discussion we have limited our attention to that variety of the word association procedure in which S is asked to associate once to a single word specified by E. Continuous association, in which E presents a single stimulus word and allows S a certain amount of time for saying as many separate words as suggest themselves, has also been employed in studies of word association. The first quantitative analysis of continuous association was undertaken by Bousfield and Sedgewick (1944) who found that the number of associations produced by 5s in the continuous association procedure could be described by the following modified exponential equation: N — C(l-e_mt), where N is the number of associates produced, m is a constant determined by the data, C is a constant which represents the total number of associates in a given cluster, and t is the amount of time given for

INTRODUCTION

21

continuous association. Explicit in their use of this function was the hypothesis that the rate of association production is some fraction of the difference between the total possible number of associations in S's repertoire, and the number of associations already emitted, i.e., dnjdt = m(C-N). The total number of associates possible is obviously never attainable and must be assumed from the seeming asymptote of association rate in any given study. A careful analysis of Bousfield and Sedgewick's data indicated that certain characteristics of the obtained function, relating number of associates to time allowed for association, differed from the one described by their rational equation. For one, the data did not conform to the theoretical prediction primarily in the early sequences produced. This initial divergence might, as Bousfield and Sedgewick suggest, be the result of overlearning and is probably connected with the extent of S"s previous experience with these words. One hypothesis presented earlier suggested that frequency of occurrence affects response availability. If this is the case, then the rate at which initial, and presumably more overlearned, associative responses are produced should be faster; exactly the result obtained by Bousfield and Sedgewick (1944). Another condition of their experiment lends further support to the hypothesis that rapidly occuring initial associative responses are the result of extensive prior learning. Pretraining, which consisted of having S's study a list of potential responses to a particular stimulus, produced on initial divergence in association rate which was greater for that verbal response category in which S's were given this initial training, i.e., in which initial frequency, and consequently, response availability, was greater. The more interesting, and for the present analysis, more crucial divergence of the obtained from the theoretical rate of association appears only in an analysis of individual records. Here the cumulative response curve is nowhere as smooth as the theoretical equation would suggest, but contains several rapidly occurring response bursts, intermingled with periods of slower response rate. These response bursts appear irregularly throughout the records

22

INTRODUCTION

of individual Ss. It is our intention to assume that these irregularly occurring response bursts represent the evocation and depletion of an associative cluster; an assumption which will be specified further at a later time. Let us now, however, turn our attention to an analysis of the relations among words based on the nature of non-word responses aroused by verbal stimuli.

B. WORDS AND REPRESENTATIONAL MEDIATION

The representational mediation hypothesis discussed in a series of articles by Osgood and his collaborators (Osgood, 1953, 1962; Osgood, Suci & Tannenbaum, 1957) involves considerations of the responses aroused by environmental stimuli; be these stimuli overt actions, objects, or words. Using the conditioning paradigm as the basic referent, they hypothesize that some "light-weight" components of the reaction aroused by an environmental object becomes conditioned to the verbal unit associated with that environmental event. The verbal unit is analogous to a CS; the environmental object is analogous to a UCS; and the response to the environmental object is analogous to the VCR. The lightweight internal representational mediation response (rm) may be thought of as composed of the least energy expending components of the compound resppnse aroused by the environmental object itself, and each of these representational responses produces its own hypothetical internal stimulus, s m , which selectively becomes associated with overt behavior in the presence of either the physical referent itself or in the presence of the verbalization of that referent. With respect to words, Osgood has hypothesized that there are constantly recurring clusters of these representational responses. In order to uncover the specific clusterings of the r m 's aroused by words, Osgood, Suci and Tannenbaum (1957) have factor-analyzed the judgments of a number of Ss rating a wide variety of stimulus materials (words, TAT cards, sonar signals, etc.) on a number of seven step scales composed of polar adjectives, i.e., good-bad. The result of a number of these factor analytic studies indicates

INTRODUCTION

23

that a good portion of the variance in rating stimuli on the seven step adjective scales is accounted for by three factors; Evaluation, Potency, and Activity. Congruence between the behavioral hypothesis and the uncovered tri-dimensional factor space is achieved by assuming that each dimension represents a cluster of similar specific r m 's, and that the strength of the r m aroused is indexed by the degree of polarization of the rating made on a given stimulus. Thus, both the characteristic quality (the dimension most strongly rated) and intensity (the degree of polarization of the rating) of a given r m is measurable by considering the S's rating of the stimulus on a number of seven step adjectival scales, called semantic differential (SD) scales.

C. CONCEPTUALIZATION OF A SEMANTIC STRUCTURE

The representational and verbal mediation approaches, by and large, have been investigated independently of each other. Yet it is apparent that they are not incompatible, and that a single conceptualization could describe both adequately. If we assume that a word arouses both conditioned meaning and verbal association responses, it is possible to conceive of an overall verbalcognitive structure in which the basic reference axes are derived from representational responses, and within which it is possible to locate verbal clusters. Thus, a single stimulus word, and those words which are its total range of word associates should have some representational mediation in common. Data relevant to support this assumption would show a positive correlation between the conditioned meaning response aroused by a word, and the conditioned meaning response aroused by its word associates. Staats and Staats (1959) report a strong positive correlation between the SD (semantic differential) rating of a word and the mean SD rating of its total range of word associates. Pollio (1964a) reports positive correlations between the SD rating of a word and the SD rating of its first associate on all three major semantic dimensions. These correlations lend some support to the hypoth-

24

INTRODUCTION

esis that a word and its word associates can be thought of as having a cognitive organization based on conditioned meaning properties. Further confirmation for the view that semantic similarly is involved in determining the characteristics of word-association is provided in an experiment by Pollio (1963b). In this experiment 5s were exposed to 3 nonsense syllables which served as CSs in the Staats and Staats (1959) language conditioning procedure. At the conclusion of the initial conditioning period, Ss were asked to produce word-associations to the previously meaningless nonsense syllables. Results showed that about 50% of all of the associates evoked by these syllables were words not originally occurring as UCS words in the initial training period. More importantly, the results also revealed that the semantic characteristics of these "cued" associates were similar to the semantic characteristics conditioned to the CS syllables. When word-word connections are unavailable, word association seems to depend upon the semantic characteristics of the stimulus word. The existence of verbal clusters is also congruent with the hypothesis that semantic factors are significant components of the cognitive organization which underlies word-association behavior. While the basic organization may depend upon the conditioned meaning responses aroused by a stimulus word, verbal clusters also markedly affect the course of overt word association. If a word is in a given cluster, then the direction of its associative tendencies is determined by the number of its intra-cluster relations, as well as by the number of inter-cluster connections which exist between itself, its cluster, and other verbal clusters. Thus, each word is located in the overall semantic space on the basis of its characteristic conditioned meaning response(s). This response has been learned through the pairing of the word with environmental situations and with other meaningful words. Early learning may be thought of as primarily connotative in nature, with the establishment of strong word-word bonds (verbal connections) occurring somewhat later. Only through relatively extensive concomitant verbal and meaning learning does the semantic space become heavily populated with words; and only

INTRODUCTION

25

then do stable verbal associative hierarchies as well as stable verbal clusters to single words, develop. If this is the case, then the verbal associations of children should more often fall in the same portion of the semantic space than is true for the verbal associations of adults. This prediction has been verified, at least as far as first associates are concerned, on all three major semantic differential dimensions (Pollio, 1964a). Perhaps, conditioned meaning is more specifically involved in determining primary verbal associations for children than for adults. With the development of verbal clusters, however, most overt verbal associative responses result from the relations which exist among the word associates themselves. We have seen on the basis of the Deese (1959a, 1959b) and Rothkopf and Coke (1961) experiments that quite precise prediction for specific words is possible, even if verbal hierarchy factors alone are considered. The present analysis does not deny a significant role to verbal associative factors. It would like, however, to emphasize that conditioned meaning factors are able to determine overt verbal behavior in the absence of direct verbal connections. Dicken (1961), for example, has demonstrated that generalization occurs across stimulus words even in the case where direct verbal connections are minimal or non-existent. Similarly, Ryan (1960) has shown that transfer may occur in the absence of direct associative connections. As we have already noted, Pollio (1963a) has also been able to demonstrate that meaningful mediation is sufficient to account for overt word association under special conditions. The overall organization of words implied by the preceding analysis is given geometric depiction in Figure 2. In this figure the overall organization of verbal clusters is in terms of fractional conditioned meaning responses. Each of the three main orthogonal axes represents one of the connotative meaning factors uncovered by Osgood et al (1957), and each point represents a single word. In this sense, each word is located in the semantic space on the basis of its representational meaning response(s). The directed lines represent the associative interconnections of an «-element cluster. Cluster I, for example, has five elements and four directed

26

INTRODUCTION

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