lay inferences of personality traits: the role of behaviour prototypicality and between-trait...

European Journal of Social Psychology, Vol. 23,255-272 (1993)

Lay inferences of personality traits: The role of behaviour prototypicality and

between-trait differences

BOGDAN WOJCISZKE, RYSZARD PIENKOWSKI, ANDRZEJ MAROSZEK, HANNA BRYCZ and MARLENA RATAJCZAK University of Gdansk, Poland

Abstract

In Study I , 60-item sets of behavioural acts exemplifying apersonality trait were elicited for each of 40 traits. Each set of behaviours was then rated by 66 students for their inferential meaning (prototypicality) and evaluative meaning (valence). As predicted, the traits difered in the degree of congruence between the two meanings of their exempli- $cations. In Study 2, 80 subjects were presented with behaviour descriptions varying in their prototypicality for congruent or incongruent traits, and were asked for trait inferences and evaluations. The higher prototypicality, the more the inferred traits were similar to the original ‘criterion’ traits and the more extreme were the ascriptions of those freely inferred traits. As predicted on the basis of accentuation theory, behaviours exemplifying congruent traits led to more extreme trait inferences and evaluations than behaviours exemplifying incongruent traits. We conclude that trait inferences and evaluations are based both on prototypicality of behavioural acts and on structural properties of the traits exemplified by these acts.

INTRODUCTION

The present research deals with the problem how people come to conclusions about traits, based on information about behaviour. The logical point of departure is, then an analysis of the trait-behaviour link, which has been conceptualized in two

Addressee for correspondence: Bogdan Wojciszke, Institute of Psychology, University of Gdansk, ul. Pomorska, 68,80-343 Gdansk, Poland The final draft of this paper was written when the first author was an Alexander von Humboldt fellow in 1991/92 at the University of Bielefeld, Germany. The research reported in the paper was supported by the CPBP 08.02 grant from the Polish Academy of Sciences. We thank Peter Borkenau, Maria Jxwicka and several reviewers for helpful suggestions, and Maria Yapp and Brenda Kopko for language revisions of earlier drafts.

0046-2772/93/020255-18$14.00 0 1993 by John Wiley & Sons, Ltd.

Received 30 May 1991 Accepted 30 June 1992

256 B. Wojciszke et al.

basic ways: as a causal relation or as an exemplification relation (Wojciszke and Pienkowski, 199 1). From the classical causal relation perspective, traits are viewed as causal entities and behaviours are viewed as their effects or at least the former are conceived as purposive dispositions, that is, forces embedded in an individual which energize, select and direct behaviours treated as their manifestations (Murray, 1938). From the exempl$cation relation perspective, traits are viewed as categories of behaviours similar in meaning, whereas behaviours are considered as exemplars of these categories (e.g. Buss and Craik, 1983).

These two perspectives imply quite different approaches to the problem of trait inferences in lay person perception. From the causal relation perspective, trait inference is equivalent to mental retraversing the original trait-behaviour causal path, from an effect (behaviour) to its cause (trait). A trait is inferred from a given behavioural act when the perceiver decides that the trait, rather than any other factor (especially a situational inducement) has caused the behaviour in question. This is, of course, the basic tenet of attribution theory. From the exemplification relation perspective, trait inference is a specific case of the categorization process where behaviour is the object of identification and the trait serves as a generic category used to categorize the behaviour. A trait is inferred from a behaviour when the perceiver decides that this particular trait catches the essential meaning of the behaviour. This is a common assumption of social cognition theories of person judgment and memory.

Trait inferences and prototypicality gradients

For several reasons, the present work adopts this second approach to trait inferences. First, judgments of causation are most probably presupposed by the more basic behaviour categorization process. Behaviour categorization, which is spontaneous (Uleman, 1989) and frequently made in trait-like terms (Bassili, 1989), seems a necess- ary precondition for the subsequent judgments of its causation (Trope, 1989) which are frequently non-spontaneous (i.e. they are not formulated if subjects are not prompted to do so by specific goals). Second, numerous trait-like labels serve their function as behaviour categorizations without implying causation (Newman and Uleman, 1989). Finally, approaching traits as categories rather than causal entities enables one to pose and answer questions about the trait internal structure and its influence on trait inferences, which is the main concern of the present work.

Trait inferences are, then, viewed as categorization processes in which an actor’s behaviours are assigned to one or more trait categories. After the act frequency approach to personality (Buss and Craik, 1983), we conceive trait categories as fuzzy sets of acts without clear-cut boundaries, where category membership is continuous rather than discrete, and particular acts differ in their status as exemplars of a category from highly prototypical to progressively more peripheral or less prototypical. Because the prototypicality gradient of behaviours reflects their varied proximity to trait concepts in semantic space (Borkenau, 1990), we predict that the higher prototypicality of an act for a trait, the higher probability that this particular trait will be inferred by the perceiver based on this act.

To test this idea, we elicited from our Study 1 subjects sets of behaviours exemplifying each of 20 positive and 20 negative traits and asked other subjects for prototypicality ratings of each set. In Study 2, we presented subjects with behaviours exemplifying

Trait inferences 251

different ‘criterion’ traits on various prototypicality levels and asked them to infer traits implied by each behaviour as well as to indicate the intensity of their trait ascriptions and evaluative impressions of persons performing the behaviours.

Three specific hypotheses were tested. First, we expected that increases in behaviour prototypicality would result in enhancement of the similarity between the freely inferred traits and the original ‘criterion’ traits. For example, the higher the prototypicality of a behaviour for honesty trait (according to our Study I), the more traits spontaneously inferred from this behaviour will be similar in content to the honesty concept. Second, the intensity of trait ascriptions was also expected to increase with the increase in the prototypicality of the stimulus behaviour. Third, a similar expectation was held for evaluative impressions: for positive (negative) behaviours we expected that the higher their prototypicality, the more positive (negative) impressions would be formulated.

Descriptive and evaluative meaning

Researchers agree that trait and/or behavioural information has both descriptive and evaluative meaning (Peabody, 1967), and that these two meaning systems operate according to different information-processing rules (Lewicka, 1979) which results in two distinct types of memory representations of another person (Srull and Wyer, 1989). The prototypicality gradient of behaviours exemplifying the same trait reflects mainly their differentiation in descriptive meaning, because the higher prototypicality of an act for a given trait, the more the trait catches the general sense of this particular act. However, because the vast majority of trait names is highly saturated with either positive or negative evaluation (Anderson, 1968), purely descriptive judgments are hardly possible in the area of personality traits. Inevitably, then, prototypicality differentiation involves to a degree also evaluative meaning. Therefore, we refer to the prototypicality gradient as tapping the inferentiul (rather than purely descriptive) meaning of behavioural acts.

However, the mere prototypicality of acts does not inform directly on their evaluative meaning, because some expressions of generally positive traits are negative, whereas some expressions of negative traits can be positive. For example, though honesty is a favourable trait, ‘Turned in a classmate for giving someone an answer in an exam’ is a negative behaviour despite its diagnosticity for honesty (Wyer and Gordon, 1982). Therefore, we asked our Study 1 subjects to estimate valence (favourability) of each behaviour in addition to its prototypicality. Having these two estimates, we were able to address two important problems.

First, we computed a correlation between the estimates of prototypicality and valence separately for each set of behaviours examplifying one trait, expecting that traits would vary in the degree to which inferential and evaluative meanings of their exemplifications are related. This expectation was based on the idea that some trait dimensions are evaluated in accordance with a simple linear rule ‘the more (of the trait), the better’, whereas others are evaluated in accordance with a more complicated ‘there can be too much of a good thing’ rule. Which of those two evaluation rules is applied to a trait depends on whether the extreme or rather a moderate intensity is most desired and received the highest evaluation. This is suggested by data of Wojciszke, Pienkowski and Tkaczyk (1992), who asked their subjects to decide which of the evaluation rules applies to each of 50 positive traits or to indicate the ideal


(most valued) intensities of those traits. The evaluation rule and the location of the trait ideal were strongly related: the more extreme a trait ideal intensity, the more its evaluation was regarded as conforming to the ‘the more, the better’ rather than to the ‘too much of a good thing’ rule.

This suggests that for some traits an increase in behaviour prototypicality should be always positive and a strong prototypicality-valence correlation may be expected in their case. We call them congruent traits, because the evaluative meanings of their exemplifications are congruent with their inferential meanings. For other traits, however, an increase in behaviour prototypicality is sometimes positive (before the ideal trait intensity is reached) but sometimes negative (after the ideal is surpassed). Prototypicality-valence correlations should be weak for those traits and we call them, accordingly, incongruent traits.

Interestingly, the congruent and incongruent traits should influence person perception processes in different ways. When the inferential and evaluative meanings of relevant behaviours are strongly related, descriptive and evaluative inferences drawn from those behaviours can strengthen each other. Trait ascriptions can be based not only on the inferential meaning of stimulus behaviours, but also on the observers’ own affective responses toward an actor performing those behaviours. Similarly, global evaluations of the actor can be based not only on the observer’s purely affective responses but also on trait inferences. This is, however, not the case for incongruent traits, where trait inferences and evaluations cannot bolster each other to such a degree, because the two behaviour meanings are not linked by a simple, linear rule.

This reasoning is derived from the accentuation theory (Eiser and Stroebe, 1972; Tajfel, 1959) which has shown that correlated variations of a set of stimuli on different dimensions lead to an increased discrimination among those stimuli. When a set of stimuli varies simultaneously on two dimensions and the two variations are systematically related, the stimuli are perceived as more differentiated on each of those dimensions than when the two variations are unrelated. In accentuation theory terms, behaviours exemplifying congruent traits are the case of two systematically correlated variations (in inferential and evaluative meanings), whereas behaviours exemplifying incongruent traits are the case of unrelated variations. Therefore, we expected that behaviours exemplifying congruent traits would lead to generally more extreme trait ascriptions and global evaluations than behaviours which exemplify incongruent traits. This prediction was tested in Study 2.

Traits related to morality and competence

The second relevant between-trait differentiation refers to a distinction between the domains of morality and competence. The schematic model of trait attribution (Reeder and Brewer, 1979) and the category-diagnosticity approach to impression formation (Skowronski and Carlston, 1987) assume interesting asymmetries between informativeness of positive and negative behaviours in these two domains. All persons including immoral ones are likely to attempt moral (socially desirable) behaviours, but only persons characterized by immoral traits are thought to attempt immoral acts. Therefore, negative behaviours are more informative with respect to possible trait inferences than the positive ones. Just the opposite is true in the ability domain. Persons characterized by high ability dispositions are the only ones capable of highly competent behaviour, while low ability behaviour is expected of anybody. Therefore,


positive behaviours are more informative with respect to competence traits than negative ones.

If the prototypicality gradient really reflects differentiation of acts in their informativeness for trait inferences, prototypicality estimates of acts exemplifying traits related to morality and competence should show similar asymmetries. The mean prototypicality should be higher for negative than positive behaviours exemplifying morality-related traits, whereas the opposite should be true for behaviours exemplifying competence-related traits.

We also expected that behaviours exemplifying moral traits would lead to more extreme evaluations than those which exemplify competence traits. This is because moral/immoral behaviours are more intentional and controllable than the competence-related ones. Therefore, the actor can be held more responsible for the former. Moreover, the actor’s morality/immorality have clear-cut hedonic consequences for the observer, whereas the consequences of the actor’s competence are more uncertain as they depend on the actor’s intentions.

STUDY 1

Study 1 served two purposes. First, it aimed at gathering materials for Study 2: Behaviour descriptions and estimates of their prototypicality and valence. Second, it tested some of the hypotheses concerning between-trait differences.

Method

Overview and subjects

At the first stage of the study, a group of 200 subjects ranging from high school students (aged 17 years) to pensioners (aged 70 years) generated behavioural acts expressing each of 60 traits initially selected for the study. This sample was intention- ally heterogeneous to obtain behaviour descriptions maximally differing in content. Forty traits which had elicited the highest number of behaviours were used in the second stage, where 1056 Gdansk University students (436 males and 620 females, aged 20-29 years) rated behaviours exemplifying particular traits for their prototypicality and valence.

Procedure

Sixty traits (30 antonymous pairs) covering a wide range of content (cf. Table 1) were selected from Lewicka’s (1983) list of Polish trait names which is similar in objectives and scope to Anderson’s (1968) list of English trait names.

Behaviour generation Each of 200 subjects received a short list of three positive and three negative traits (containing no semantic opposites) and was asked to think up 10 behaviours exemplifying each trait. The content and order of consecutive sublists were varied systematically in such a way, that each particular trait appeared on 20 different sublists (i.e. in 20 different contexts of other five traits) and each of the 60 traits was responded to by 20 different subjects.

Despite the instructions, many of the responses contained no actual descriptions


of behaviour but single words, mainly adjectives synonymous to the criterion trait- names. Therefore, we decided to exclude 20 traits which had elicited the lowest (32 or less) amount of behaviours from the subjects. For the remaining 40 traits (cf. Table 1) behaviour descriptions were supplemented up to 60 per trait by means of a panel discussion of the present authors (with subjects’ original but ‘abortive’ responses serving as cues for the panel)’. The resulting set consisted of 2400 behaviour descriptions, such as ‘John had an extramarital affair’ or ‘Seeing an opportunity to steal goods in a supermarket, Mary did so’ (trait dishonesty).

Prototypicality and valence ratings The ratings were made in sets consisting of one trait (e.g. honesty) and 60 behaviours expressing that particular trait. When rating prototypicality, subjects answered the following question (worded here for honesty): ‘To what extent is each of these behaviours a typical example of honesty, that is, how much could you say about a person’s honesty based on this behaviour alone?’ Subjects indicated their judgements on a scale ranging from 0 (next to nothing can be said / very atypical expression of honesty) to 6 (very much can be said / very typical expression of honesty). When subjects had finished these ratings, they were asked to estimate valence of these behaviours, that is, whether each behaviour implied positive or negative evaluation of its actor, on a scale ranging from -3 to 0 to +3.

There were male and female versions of each 60-item set (which was manipulated by an actor’s name). Each version was rated by 33 subjects. Altogether, then, behaviours exemplifying each trait were rated by 66 subjects. Initial analyses showed no systematic effects of the actor’s sex and this factor is omitted in the further presentation. Having solved their first set, subjects could volunteer for further (semantically unrelated) sets, as many as they wished, though only up to four sets coming from the same subject were analysed. Thereby, each subject rated from one to four (2.51 on the average) different sets, which enabled us to reduce the sample size.

Results and discussion

Prototypicality ratings

As can be seen in Table 1, average prototypicality ratings were higher for behaviours exemplifying positive (3.85) rather than negative (3.65) traits, t (38) =2.06, p < 0.05. To estimate reliability of the prototypicality ratings we followed other authors (Borkenau, 1986) and employed the intraclass correlation coefficient [ICC(2,k) according to Shrout and Fleiss (1979), where k stands for the number of judges which was 66 for each trait from Table 11. The obtained coefficients were invariably high (only for one trait was the coefficient below 0.80), and marginally higher for negative than positive traits, t (38) = 1.95, p < 0.07 (two-tailed test)2.

’ The number of behaviours supplemented by the researchers varied from 28 to 16 for different traits (24.05 on the average). It should be noted, that the ‘failure’ of our subjects to generate a greater amount of behaviour descriptions is similar to what has been reported by other authors in the area (e.g. Buss and Craik, 1983, 1984). The relatively low number of acts generated by ‘ordinary’ (untrained) subjects is cumberstone from the perspective of great hopes associated with the ‘act nomination procedure’ by proponents of the act frequency approach to personality ( c j Buss and Craik, 1983). However, no prediction of the present study demands behaviour descriptions coming specifically from subjects but not from researchers.

In all computations involving r or ICC correlation coefficients, Fisher’s z transformation was used.


Table 1. The traits searched in Study 1 and their main parameters

Protol valence Trait Prototypicality Valence

Trait Mean ICC Mean ICC correl. standard

Positive traits 1. Cheerful 2. Courageous 3. Critical 4. Friendly 5. Honest 6. Industrious 7. Ingenious 8. Intelligent 9. Just

10. Loyal 11. Modest 12. Patient 13. Resourceful 14. Responsible 15. Sincere 16. Sociable 17. Systematic 18. Tolerant 19. Trustful 20. Will power Positive (means)

Negative traits 1. Sad 2. Coward 3. Uncritical 4. Hostile 5. Dishonest 6. Lazy 7. Calculating 8. Unintelligent 9. Unjust

10. Disloyal 11. Conceited 12. Impatient 13. Unresourceful 14. Irresponsible 15. Insincere 16. Unsociable 17. Chaotic 18. Intolerant 19. Suspicious 20. Lacking of will Negative (means)

3.35 3.46 3.95 3.62 3.95 4.10 4.05 3.85 3.71 4.05 3.70 3.93 4.11 4.00 3.88 3.90 3.76 4.00 3.78 3.90 3.85

3.01 3.23 3.41 3.63 4.00 3.59 3.56 3.41 4.04 4.23 3.86 3.76 3.36 4.18 3.74 2.70 3.55 4.18 3.85 3.63 3.65

0.93 0.91 0.84 0.85 0.93 0.85 0.84 0.87 0.86 0.83 0.84 0.86 0.90 0.87 0.81 0.88 0.89 0.68 0.92 0.89 0.87

0.86 0.91 0.85 0.89 0.90 0.91 0.95 0.81 0.86 0.92 0.92 0.91 0.86 0.89 0.95 0.93 0.87 0.84 0.92 0.86 0.90

1.23 1.11 1.72 1.97 1.47 1.42 2.00 1.59 1.76 1.75 0.83 1.17 1.50 1.95 1.31 1.44 1.41 1.11

-0.02 1.44 1.41

-1.09 -0.83 -0.88 -1.69 -1.91 - 1.42 -0.73 -1.37 -1.51 -2.03 -1.17 -0.93 -1.13 -2.01 - 1.29 -0.46 -1.21 -1.27 -0.82 -1.21 - 1.25

0.96 0.98 0.92 0.89 0.96 0.92 0.86 0.91 0.89 0.91 0.91 0.96 0.98 0.86 0.94 0.95 0.96 0.95 0.96 0.96 0.94

0.90 0.95 0.94 0.93 0.90 0.88 0.98 0.90 0.83 0.94 0.94 0.97 0.91 0.92 0.96 0.94 0.89 0.92 0.94 0.91 0.93

0.48* 0.44* 0.43* 0.78* 0.63* 0.16 0.80* 0.66* 0.67* 0.64* 0.18 0.17 0.38* 0.83* 0.17 0.62* 0.68*

-0.12 0.00 0.62* 0.51*

-0.47* -0.60* -0.75* -0.69* -0.91* -0.84* -0.90* -0.74* -0.90* -0.89* -0.79* -0.42* -0.91* -0.83* -0.89* -0.92* -0.72* -0.65* -0.58* -0.62* -0.79*

9.9 11.7 9.3

12.4 12.8 10.6 12.9 13.3 13.7 13.9 7.7 9.6

12.1 14.5 10.9 10.2 10.5 10.3 6.6

14.4 11.4

3.2 1.6 1.9 1.5 1.9 3.1 2.9 1.4 0.6 0.5 3.8 2.4 2.2 0.6 2.7 4.1 3.0 2.7 2.4 1.2 2.2 -

Antonymous pairs share the same number. All intraclass correlations (ZCC) are significant at p < 0.001. * p < 0.01.


Valence ratings

Similar analyses performed on valence ratings evidenced of course a theoretically trivial effect of the trait sign (behaviours exemplifying positive traits had positive valence, whereas behaviours exemplifying negative traits had negative valence). Relia- bility of valence ratings was high independent of the trait sign (cf. Table 1).

Congruence of inferential and evaluative meaning

Congruence of inferential and evaluative meaning was estimated separately for each trait by Pearson’s r correlation between mean ratings of prototypicality and valence of the successive (60) behaviours exemplifying this trait. As can be seen in the fifth column of Table 1, the traits differed greatly in congruence of the two behavior meanings. Interestingly, all traits for which no linear relation between the two meaning was found were positive, and the absolute value of prototypicality-valence correlation was much greater for negative (0.79) than positive (-0.51) traits, t (38) = 4.37, p < 0.001. When an actor’s behaviour increases in prototypicality for a negative trait, negativity of the actor evaluation increases straightforwardly and inevitably. For positive traits, however, similar increases in prototypicality result in the evaluation enhancement which is neither so strong nor unexceptional.

To test the role of ideal trait intensities (predicted to underlie between-trait differences in congruence), we gathered their estimates for all Table 1 traits. Twenty-six university students were asked to imagine minimal and maximal intensities of successive traits and to indicate the optimal, most desired intensity of each trait on a graphical 15 cm-long scale (the responses were measured in centimetres from the left, minimal- intensity extreme). Average trait standards are presented in the last column of Table 1. Positive trait standards were located much higher (11.37 on the average) than negative trait standards (2.18). The latter were also quite close to the minimal extreme of trait intensity and their variance (1.01) was smaller than the variance of positive trait standards (4.54) a t p < 0.05 (Snedecor’s test).

Understandably, negative trait standards are uniformly and extremely low. In some cases, however, they are well above zero suggesting that low levels of those qualities are accepted or even desired by subjects (probably because the total lack of them implies negative attributes, e.g. a person entirely lacking conceitedness may be seen as insecure or self-deprecating). In positive traits, the standards are generally high though for some traits they are moderate, probably because extreme levels of these traits imply undesirable qualities (e.g. very trusdstful person may be foolishly credulous). Our reasoning implies that the trait standard is positively related to the strength of prototypicality-valence correlation. Accordingly, we computed a correlation between those two variables (i.e. the two last columns of Table 1). Because both of them have a bimodal distribution, a nonparametric measure was employed. The correlation was tau ( N = 40) = 0.66, p < 0.01 for the whole trait sample (and tau ( N = 20) = 0.50, p < 0.01, for positive traits alone). This suggests an important role of the trait standard for the congruence between inferential and evaluative meaning of its behavioural exemplifications.

Morality-competence differences

The prototypicality ratings were generally higher for behaviours exemplifying positive rather than negative traits. However, if prototypicality reflects variation of acts in


their informativeness for trait inferences, this difference should actually hold only for competence traits, where the opposite should be true for moral traits. To verify this hypothesis, six positive (friendly, honest, just, loyal, response and tolerant) and six antonymous negative traits representing the morality domain were selected from the list displayed in Table 1, as well as six positive (critical, courageous, industrious, intelligent, resourceful and will power) and six negative antonymous traits typical for the competence domain3. Mean prototypicality ratings of behaviours expressing these traits were subjected to a 2 (morality versus competence domain) X 2 (positive versus negative trait sign) ANOVA.

This analysis revealed the predicted domain X trait sign interaction, F (1,20) = 14.08, p < 0.001. In the competence domain the mean prototypicality was higher for behaviours expressing positive (3.90) rather than negative (3.44) traits, whereas in the morality domain the opposite tendency emerged (3.89 versus 4.04). This pattern is virtually identical to the results of Skowronski and Carlston (1987), who estimated diagnosticity (rather than prototypicality) of positive and negative behaviours referring to honesty and intelligence.

Behaviours expressing moral traits were also predicted to elicit more extreme evaluations than those which exemplified competence traits. Consistent with this prediction, a 2 (morality versus competence) x 2 (positive versus negative) ANOVA performed on mean valence ratings of the same set of 24 traits revealed a significant domain x sign interaction, F(1,20) = 12 .65 ,~ < 0.002. The valence of acts exemplifying moral traits was more extreme than valence of behaviours expressing competence traits, both for positive (1.67 versus 1.46) and negative (- 1.73 versus - 1.14) traits. Thus, in addition to differential informativeness of positive and negative behaviours, the ability-morality distinction involves also an evaluative difference. Behaviours exemplifying moral traits instigate generally more extreme evaluation than those which pertain to ability traits.

STUDY 2

Although Study 1 shows high reliability of prototypicality ratings for a wide range of personality traits, results of this type do not provide a decisive test of psychological reality of the prototypicality structure of traits. It can be argued that the very relation between traits and behaviours was rather artificially superimposed on the behaviour interpretation process. The problem is that subjects might not have inferred a trait from a behavior, if the trait had not been provided by the researchers (as different traits may be inferred from the same act, cf. Angleitner and Demtroder, 1988). More- over, rating acts for their prototypicality for a specified trait hardly resembles person perception processes in natural settings.

Study 2 attempted to show prototypicality effects in a task which was both more similar to a real-life interpretation of behaviour and which did not superimpose on this process any trait names supplied by a researcher. Subjects were presented with pairs of behaviours, each of them exemplifying a ‘criterion’ trait on one of

The selection was based on ratings of traits for the extent that each of them referred to skills and/or abilities (made by 40 subjects on a scale ranging from 0 to 6 ) or to morality (made by 34 subjects). The average morality rating for the traits selected as typical for the morality domain was 4.72 but 2.71 for the traits selected as typical for the ability domain. The average ability ratings were 2.62 and 4.45, respectively.


six prototypicality levels, and were asked for their impressions of the target persons who ostensibly performed those behaviours. Specifically, they were asked to infer a trait, then to indicate the extent that they attributed the trait to the actor, and finally, to indicate their global evaluation of the actor. As discussed in the Introduc- tion, we predicted that the more prototypical a behaviour, the more similar an inferred trait would be to the original ‘criterion’ trait and the more extreme would be the trait ascriptions and evaluative impressions.

Behaviours exemplifying 16 traits were used, half of them referring to congruent and half to incongruent traits. As previously discussed, we expected that behaviours exemplifying congruent traits would lead to more extreme trait inferences and evaluations than behaviours exemplifying incongruent traits.

Method

Subjects

Thirty-one male and 49 female high school students aged 18-19 years participated in three approximately equal groups.

Materials

Trait selection Eight positive and eight negative traits were selected from the trait sample used in Study 1 . A half of positive traits (intelligent, responsible, systematic and loyal) were congruent and another half were incongruent (industrious, resourceful, trustful and sincere). The same applied to negative traits, half of which were congruent (unsociable, unjust, ineffective and calculating), while the remaining four (lacking of will power, intolerant, chaotic and impatient) were incongruent. Four replications per each sign/congruence combination were introduced to disentangle effects of congruence from the specific trait contents. Whereas two traits within each combination were strong in their global favourability (e.g. intelligent and responsible), the other two were relatively weak in favourability (e.g. systematic and loyal) (the estimates of trait favourability were borrowed from the already mentioned Lewicka list of traits). Finally, two traits of each combination referred more to competence than morality (e.g. intelligent and systematic), whereas the remainder referred more to morality than competence (e.g. responsible and loyal).

Six pairs of behaviours were selected for each trait, every pair representing one prototypicality level. Level I was always represented by two behaviours of the lowest, and level VI by two behaviours of the highest prototypicality estimates for respective traits. The remaining levels were selected in such a way, that for every trait the whole range of prototypicality ratings was cut into five approximately equal intervals.

A 2 (trait sign) x 2 (trait congruence) x (level) ANOVA was performed on prototypicality estimates of the input pairs of behaviours. This analysis showed of course a strong main effect of prototypicality with means amounting to 2.31, 2.91, 3.27, 3.79, 4.31, and 4.78 on successive levels. The prototypicality level interacted neither with the trait sign nor the congruence. Similar ANOVA for valence ratings of input pairs of behaviours revealed the intended main effect of the trait sign and its interac-

Selection of behaviours


tion with the prototypicality level. With an increase in prototypicality, the valence of input behaviours increased for positive traits (0.81, 0.88, 1.39, 1.35, 1.70, and 1.84),butdecreasedfornegativeones(0.24, -0.56, -0.69, -1.14, -1.61,and -1.87).

Procedure and dependent measures

Each subject received a booklet containing 24 randomly ordered, two-behaviour descriptions of different male target persons. Subjects were asked to treat each description separately and to think about possible personality traits underlying successive pairs of behaviours. Space was provided next to each description, where subjects were to write down a trait they inferred from the behaviours.

When the study was completed, two independent judges blind to the prototypicality conditions rated each elicited trait-name for its similarity in content to the original criterion trait. The judges used scales ranging from - 3 (completely dissimilar), to 0 (neither similar nor dissimilar) to + 3 (entirely similar) and were asked to employ a stringent criterion of similarity. Because the between-rater consistency appeared substantial ( r correlations varied for different traits from 0.45 to 0.89 with a median 0.74), ratings of the two judges were averaged yielding the index of content similarity between a trait inferred by a subject and an original criterion trait.

The number of ‘hit’ inferences, that is, the number of inferred trait names identical to the original criterion names, served as an additional measure of the descriptive similarity of the inferred traits (e.g. for behaviours exemplifying intelligence ‘intelligence’ or ‘intelligent were scored, but not ‘wise’ or ‘brilliant’).

At the next stage subjects went through the descriptions for the second time, deciding the degree to which each actor was characterized by a trait that they them- selves had previously inferred and written. To this end, subjects were provided with rating scales ranging from 1 (extremely low intensity of a trait) to 7 (extremely high intensity) on which they marked their successive attributions. These ratings served as the trait ascription index. The subjects were also asked for their evaluative impression of each actor on a scale ranging from -5 to 0 to +5. Random half of the subjects rated their evaluative impressions before the trait ascriptions.

Design

The full design included three between-subject factors (congruent versus incongruent traits, a between-subject replication of the trait content, and the task order: trait ascription first versus evaluative impression first) with 10 subjects per cell, and three within-subject factors (the trait sign, a within-subject replication of the trait content, and the prototypicality level). Twenty-four descriptions responded by a single subject referred to four different traits none of which were antonymous. The task order played no important role and therefore is omitted in the further presentation. The replications of trait contents served mainly the methodological purposes and the presentation of their effects is also dropped because of their little theoretical relevance. However, nearly all of the prototypicality effects presented below remained reliable even when computed separately for particular traits.


Results and discussion

Pro to typ icality efsec ts

Four consecutive ANOVAs were performed on the indices of content similarity, hit inferences, evaluative impressions and trait ascriptions.

The analysis of content similarity showed a strong main effect of behaviour prototypicality, F(5,360) = 44 .82 ,~ < 0.0001 : the higher the prototypicality, the more similar were the freely inferred traits to the respective criterion traits (for both positive and negative traits, cf. Table 2). The highly significant linear trend accounted for 32 per cent of variance. A similar effect was also found for the number of hit inferences, F(5,360) = 14.09, p < 0.0001.

Table 2. The influence of behaviour prototypicality on the similarity of inferred traits to their appropriate criterion traits, the proportion of hit inferences, evaluative impressions, and trait ascriptions (Study 2)

Prototypicality level Dependent measure I I1 I11 IV V vr Negative traits

Content similarity 0.99 1.36 1.56 1.43 1.56 1.71 Hit inferences 0.07 0.12 0.16 0.14 0.21 0.23 Evaluation 0.52 -0.90 -1.25 -1.90 -2.59 -3.12 Trait ascription 4.35 4.30 4.51 4.60 4.98 5.35

Positive traits Content similarity 0.56 1.32 1.29 1.48 1.85 1.73 Hit inferences 0.10 0.14 0.16 0.19 0.24 0.26 Evaluation 1.38 1.56 2.32 2.49 2.70 3.15 Trait ascription 4.20 4.60 4.63 4.64 5.27 5.50

The analysis of evaluative impressions revealed both a main effect of the trait sign, F (1,72) = 556.88, p < 0.0001, and the trait sign X prototypicality interaction, F(5,360) = 108.16,~ < 0.0001. Behaviours exemplifyingpositive traits led to generally positive evaluations, while behaviours exemplifying negative traits resulted in negative evaluations, and this difference increased with the prototypicality level. The relation between prototypicality and evaluations was linear for both positive and negative behaviours (the linear trend accounted for 20 per cent and 42 per cent of variance, respectively).

Finally, a prototypicality main effect was found for the trait ascriptions, F (5,360) =45.50, p < 0.0001. The higher the prototypicality, the more extreme were the ascriptions of the previously inferred traits. This relation too was linear, with the linear trend accounting for 30 per cent of variance4.

All those prototypicality effects were replicated in a smaller study ( N = 40), where subjects responded to one-behaviour rather than two-behaviour descriptions of target persons. The traits used in that study (honesty, dishonesty, intelligence, lack of intelligence, patience, impatience, truslfulness and suspiciousness) were exemplified on three prototypicality levels.


Congruence between inferential and evaluative meaning

The analysis of trait ascriptions revealed also the expected main effect of trait congruence, F (1,72) = 4.42, p < 0.05; with trait ascriptions being more extreme when based on behaviours exemplifying congruent rather than incongruent traits (4.97 versus 4.53). An interaction between the trait congruence and sign was nonsignificant, F < 1, suggesting that the effect of congruence holds with equal strength for positive and negative traits. However, the congruence X trait sign interaction emerged where it was expected, that is, for the measure of evaluative impressions, F (1,72) = 16.63, p < 0.001. Evaluations were more extreme for the congruent than incongruent traits, both for the positive (2.75 versus 1.80) and negative (- 1.74 versus - 1.34) behavioural information.

This result is entirely in line with our idea that when behaviours exemplify congruent traits, the descriptive and evaluative inferences from those behaviours can strengthen each other. Importantly, none of these effects had been found for the prototypicality or valence estimates of the input behaviour descriptions. This suggests that instead of simply following the parameters of stimulus information, the reported effects truly reflect the differentiation of congruent and incongruent traits in their structural properties (i.e. the degree of consistency between inferential and evaluative meaning of their behavioural exemplifications).

GENERAL DISCUSSION

Taken together, the present results show considerable support for the validity of the prototypicality approach to the structure of personality traits as cognitive categories and offer some insight into the way in which those categories influence the process of person perception.

Prototypicality structure of traits

The prototypicality structure seems to be quite a general phenomenon in the area of personality trait concepts. When estimated by relatively large samples, prototypicality ratings show generally high reliability. These results are in line with the act frequency approach (AFA) findings (Angleitner, Buss and Demtroder, 1990; Buss and Craik, 1983) and offer a replication with a different content of behaviours, a different language and for a wide range of traits.

The AFA has been suggested as a novel perspective to assess dispositions and to study personality processes (Buss and Craik, 1983, 1984). For instance, the frequency of behavioural acts prototypical for a disposition tallied over a specified period of time has been suggested to yield an absolute estimate of trait level which would pave the way to solve empirically such important problems as the assessment of dispositional consistency and stability or the idiographic analysis of personality. Those ambitious AFA claims have been severely criticized, however, especially to study retrospective self-reports instead of actual behavioural acts, and to replace explanations of personality by its pure description (Block, 1989). This criticism suggests that the AFA is probably not the best intellectual equipment for scientific assessment and explanation of personality dispositions.

From its very beginning, however, the AFA offered not only a way to understand


human dispositions in personality assessment, but also a way to understand traits as cognitive categories in lay person perception (and most AFA findings should probably be seen as referring to the latter rather than the former). Study 2 suggest that the AFA account of the internal structure of traits as cognitive categories results in reliable predictions concerning the prototypicality gradient in lay person perception. The higher the prototypicality, of the behavioural information the more similar are the generated traits to that trait for which the prototypicality ratings had been originally made. Intensity of trait ascriptions and evaluative impressions follows linearly the same prototypicality-based pattern.

In respect of trait ascriptions, this is similar to results obtained by Borkenau (1990) and Read, Jones and Miller (1990), who asked their subjects to ascribe some provided traits on the basis of behaviours varying in prototypicality for those traits. Such a task, however, involves processes which are probably different from those investigated in the present Study 2. When ready-made categories are provided to subjects, trait inferences amount to trait-behaviour matching (how much this particular behaviour is similar to this specific trait?). This is similar to the prototypicality judgment procedure, where traits are also given in advance. However, providing subjects with ready-made categories induces behaviour interpretation driven by exactly those categories which, in turn, leads to overestimation of the degree to which behavioural acts instantiate those pre-activated categories (cf. Higgins, 1989). This may explain, for example, the almost perfect correlations between trait ascriptions and behaviour prototypicality reported by Borkenau (1990, p. 386). Such a biased interpretation is, however, impossible when trait inferences are not predeter- mined by superimposed categories, as in Study 2, where trait inferences probably involved behaviour-trait matching (which trait is similar to those particular behavioural acts?). Study 2 shows, then, the inferential power of prototypicality gradients and their psychological reality in the unconstrained-inference context, where prototypicality effects cannot be explained as a result of the biased behaviour interpretation.

The effects found in Study 2 may be easily explained in terms of semantic relatedness between behavioural acts and personality traits exemplified by them. Prototypicality- based explanations are generally hard to distinguish empirically from those based on the semantic relatedness notion (Semin and Rosch, 1981). However, in the person perception area the notion itself is so general and vague that it better suits post-hoc explanations than inspires specific problems and predictions. Perhaps the best solu- tion is to conceive the prototypicality gradient as a specific case of semantic relatedness, as proposed recently by Borkenau (1990). According to his theory of semantic space, acts, traits and personality impressions are located in a common semantic space. Whereas the prototypicality dimension taps the semantic proximity between acts (instances) and traits (categories), semantic similarity refers to distances among traits. Personality impressions, in turn, reflect the semantic coordinates of the information about acts performed by the target person, and trait inferences follow semantic distances between an impression and traits. Therefore, if ‘personality impressions are semantically close to the meaning of a trait term, the persons are judged to be high on that trait’ (Borkenau, 1990, p. 381). This assertion is directly supported by the present findings of prototypicality effects in trait inferences and evaluations. Virtue of this support lies, we believe, in its immunity to a criticism which may be applied to Borkenau’s original results, that the researcher-provided traits bias behaviour interpretation and the resulting trait ascriptions.


On the other hand, the between-trait differences discussed below suggest that the concept of semantic relatedness refers to a phenomenon which may be not unitary in its nature. Acts, traits and impressions can vary in their both descriptive and evaluative similarity, and the two kinds of semantic proximity do not overlap entirely, which has important consequences for person perception processes.

Differentiation of traits as cognitive categories

‘Not all traits are created equal’ asserts Schneider (1991) in his recent review of the relevant literature. Present results speak to the same point.

First, using prototypicality estimates in Study 1, we were able to replicate the positive-negative asymmetries between morality and competence domains which Skowronski and Carlston (1987) directly tapped by diagnosticity measuress. Valence estimates of behaviours from Study 1 showed an additional morality-competence difference: others’ behaviour referring to their morality/immorality instigates more extreme evaluations than their behaviour showing competencehcompetence.

Second, computing the congruence between inferential and evaluative meaning of behaviours which exemplified successive traits, we were able to show that traits differ widely in this respect. This is an interesting finding, since there is a controversy concerning the relation between trait intensity and its affective value. A linear relation between increasing trait intensity and corresponding evaluative impressions is assumed explicitly (e.g. Anderson, 198 1, p. 280) or implicitly by most person perception theories. On the other hand, Aristotle maintained in his Nikomacheian Ethics that true virtue is found in moderation, whereas both insufficiency and overabundance are erroneous. Much more recently, Peabody (1967) postulated a curvilinear relation between attribute intensity and its affective value, believing that the ‘extremes are evaluated negatively’ rule is universal, although his own data supported this idea only for some traits.

Our data suggest that at least for positive traits both the linear (‘the more, the better’) and curvilinear (‘too much of a good thing’) rules may be true, although for different traits. Location of the ideal trait intensity seems to be an important factor deciding which of the two rules prevails. However, the inspection of Table 1 suggests that the traits of low prototypicality-valence correlations are also relatively moderate in their general favourability. Indeed, the correlation between the prototypicality-valence congruence, and estimates of trait favourability (borrowed from Lew- icka’s list of Polish trait-names) was tau ( N = 40) = 0.73, p < 0.001. Clearly, the level of congruence may depend on the global favourability of a trait.

This is not to say, that behaviour prototypicality and its diagnosticity for a trait are the same. Direct diagnosticity measures should involve both an estimate of the degree to which a behaviour is related to the trait in question and an estimate of the degree to which it is unrelated to alternative traits (cf. Skowronski and Carlston, 1987; Smith and Medin, 1981), whereas prototypicality measures involve only the former. This would speak to superiority of diagnosticity measures if it was not very hard to decide in numerous contexts which traits are alternatives for the trait in question. For example, for punctual, the trait unpunctual seems to be a logical choice, but the problem is that behaviours exemplifying punctuality exemplify also semantically similar traits, such as precise or orderly (cf. Angleitner and Demtoder, 1988; Borkenau, 1986), as well as traits which hierarchically include punctuality, such as dutiful, or, on a more abstract level, responsible (Hampson, John and Goldberg, 1986). It is not clear, which of those other traits should not be exemplified by a behaviour highly diagnostic for punctuality. Generally speaking, diagnosticity measures seem to be adequate mainly in contexts where only a single alternative exists for the categorization in question whereas prototypicality measures seem free of this constraint.


Every trait may be regarded as containing some mixture of positive and negative features (e.g. tolerance implies forbearance but also some impassivity). The proportion of positive and negative features is likely to determine a trait’s general favourability. Increases in global trait intensity are probably accompanied by corresponding increases in both positive and negative features relevant for the trait in question. However, it is well-established that the negative value of costs increases faster than the positive value of gains (Atthowe, 1960; Myers, Reilly and Taub, 1961). Therefore, for mildly positive traits which contain positive as well as some negative features, beneficial effects of increases in positivity may be offset by harmful effects of the parallel increases in negativity (e.g. the charm of forebearance resulting from an increased tolerance can be overcome by the impassivity coming from the same source). This mechanism may be responsible for the dilution of the linear relation between trait intensity and its value for mildly favourable traits.

On the other hand, extremely positive traits contain many positive but few negative features. The proportion of the latter can be so small, that the beneficial effects of positive features are not overcome by the harmful effects of negative features even at the extreme trait intensities (as in the case of dependability, which hardly involves negative features even on its extreme level). For extremely favourable traits, positive features always prevail over negative ones, and this may account for the invariably linear intensityhalue relation among them (and the same applies for extremely unfavourable traits, where negative features invariably prevail over the positive ones).

The present research cannot decide which of the two mechanisms (differential location of the trait standard or differential accumulation of the trait positive and negative implications) mediates the between-trait differences in congruence between inferential and evaluative meaning of their behavioural exemplifications. Neverthe- less, Study 2 suggests that the degree of such congruence significantly influences person impressions. Behaviours exemplifying congruent traits led to more extreme trait inferences and evaluations than behaviours which exemplified incongruent traits.

This result contributes to the vast literature showing that person impressions depend on the cognitive categories which are applied by the observer to the stimulus information (cJ: Higgins, 1989). However, whereas the bulk of this literature shows the decisive role of category content, the present research suggests that purely structural properties of traits contribute substantially to person impressions in addition to specific contents of both the perceiver’s categories and stimulus information. Because the variation of traits in their structural properties is probably smaller than their possible variation in contents, focus on structural properties may help to formu- late more parsimonious explanations of trait influences on person perception processes.

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