positive-negative asymmetry in normative data

European Journal of Social Psychology, Vol. 22,483496 (1992)

Positive-negative asymmetry in normative data

A. P. TUOHY Department of Psychology, Glasgow Polytechnic, Glasgo w G4 OBA, U. K.

and

S. G. STRADLING Department of Psychology, University of Manchester, Manchester MI3 9PL, U.K.

Abstract

Three samples, consisting of 200 traits, 200 nouns and 200 verbs taken from the TogIia et al. (1978) verbal norms, were analysed for evidence of positive-negative asymmetry. Within each sample the items were ordered on a general positive-negative index, and a systematic series of dichotomizations was carried out, ranging from Sper cent negative to 95 per cent negative. It was found that the partial correlation of pleasingness with the positive-negative dichotomization increased as a linear function of the informational complexity of the negative class of words, for all three word types. The partial correlation of familiarity increased as a similar function of the positive class of words, but only for traits. The results are discussed in terms of Peeters and Czapinski’s (1990) positive- negative asymmetry model, and Scherer ’s (1984) component model of emotion.

INTRODUCTION

The distinction between positive and negative valences plays an important part in psychological functioning, exerting asymmetrical effects on various aspects of cognition, judgment and behaviour (e.g. Blaney, 1986; Boucher and Osgood, 1969; Isen, 1984; M a t h and Stang, 1978; Mayer, 1986). These effects have sometimes been discussed in terms of an interaction between affective state and the evaluative status of stimuli (e.g. Isen, Johnson, Mertz and Robinson, 1985); however, they have also been seen as arising from a psychological dichotomy rather more fundamental than evaluative judgment per se; underpinning for example all three dimensions of the semantic differential so that high Evaluation, Potency and Activity values are all comparably positive, and low values all comparably negative (Osgood, 1979; Osgood and Richards, 1973). In a recent review, Peeters and Czapinski (1990) speculated that asymmetries across this most basic dichotomy may be derived from the adaptive distinction between approach and avoidance behaviour, which necessitates not only

0046-2772/92/050483-14$12.00 0 1992 by John Wiley & Sons, Ltd.

Received 28 January 1991 Accepted 15 January 1992

484 A. P. Tuohy and S. G. Stradling

a fundamental differentiation of the environment on this generalized positive-negative criterion, but also the ability to modulate a number of distinct asymmetrical tendencies, including both positivity and negativity biases, in response to different situational demands.

Applying this ‘behavioural-adaptive’ perspective, Peeters and Czapinski proposed that some form of positivity bias or biases must be considered as essential to induce sufficient interaction with the environment, which in most situations contains ‘a greater potential for detrimental than for beneficial interaction outcomes’ (1990, p.37). By this argument, in order to deal actively with the environment at all, orga- nisms must naturally tend towards ‘optimism’ (cf. Boucher and Osgood, 1969). Peeters and Czapinski distinguished between two forms of positivity bias, both of which were conceived as contributing to the ‘approach’ aspect of the adaptive argument: a restricted positivity bias initiates approaches to the established repertoire of familiar stimulus events in safe environments, while a generalized positivity bias leads the organism to approach novel events and stimuli, with a view to expanding the range of established, known positivity. As against these two forms of positivity bias, and partly because of the larger environmental potential for negativity, Peeters and Czapinski argued that an opposite, moderating tendency must also be hypothesized, which can govern the ‘avoidance’ aspect of the argument in the form of a negativity bias or biases. Specifically, they suggested that ‘the tendency to expect the positive is allied with a strongly marked sensitivity for aversive stimuli resulting in a subjective overemphasis of the negative’ (1990, p. 37), since otherwise the effect of unmoderated positivity biases would be to lead the organism into too many detrimental situations. Their model can therefore be characterized as bi-directional in structure, since it postulates two or more oppositional tendencies towards either end of the positive-negative dimension.

Some possible evidence for the moderating negativity bias is found in the general negativity e fect (Kanouse and Hanson, 197 I), which can be broadly defined in terms of the greater subjective weight or importance often assigned to negative aspects of a stimulus than to (equally intense) positive aspects (cf . Frijda’s (1988) ‘law of hedonic asymmetry’). As Peeters and Czapinski pointed out, various bodies of evidence have been cited in support of this general effect. It is well documented, for instance, that in the integration of information in impression formation negatively signed components are more heavily weighted than positive (Anderson, 198 1; Kenrick and Stringfield, 1980). In decision under risk, prospect theory (Kahneman and Tversky, 1979) is fundamentally underpinned by the fact that perceived potential costs are typically more heavily weighted than perceived potential gains, across a broad range of judgmental situations (Tversky, Sattath and Slovic, 1988). Another type of evidence adduced by Peeters and Czapinski may be found in the literature on lexical marking (Benjafield, I983; M a t h and Stang, 1978; Osgood and Richards, 1973); the marked members of polar opposites are usually negative (e.g. ‘kind- unkind’), since this function of lexical marking denotes a deficit in or absence of the appropriate quality. This may suggest that the positive pole of a linguistic construct is often structurally simpler, with negativity representing a more complex overlay, and that the greater subjective weighting often assigned to negative aspects may therefore be in part an objective tendency, as a reaction to this potentially greater level of complexity.

In the context of this last suggestion, Peeters and Czapinski cited a range ofevidence

Asymmetry in normative data 485

to show that ‘negative stimuli elicit more cognitive work’, ‘lead to more complex cognitive representations’, and ‘are really more informative’ (1990, pp. 4647). This view seems to converge with a body of research which has defined an apparent positivity bias (i.e. a systematic enhancement of the frequency of positive responses) but has then demonstrated that in terms of its hypothetical underlying processes this effect is in fact a psychological negativity bias (Adams-Webber, 1979; Benjafield, 1985). The apparent paradox that a preponderance of positive responses constitutes a negativity bias is resolved by the fact that the minor pole of a response dichotomy makes a greater contribution to average uncertainty (Berlyne, 1971). This line of research suggests that dichotomous response sets which show a preponderance of positives may arise from hypothetical internal processes which informationally emphasize the class of negative responses. As was originally suggested by Benjafield and Adams-Webber (1976), such a tendency would be adaptive in a way which seems highly consistent with the views of Peeters and Czapinski.

Where an inconsistency does seem to arise, however, is in the logical implications of the directional reversal which springs from the use of the informational index. If the smaller class of responses (by relative frequency) is in fact more complex (by contribution to average uncertainty) and hence psychologically predominant for positive-negative asymmetry in one direction, it should be so for the other direction as well, unless quite different mechanisms are proposed. If this argument were supported by experimental investigation, the greater part of the positivity argument would have to be turned around, and the bi-directional model defined by Peeters and Czapinski would have to be adjusted in detail.

A number of potential revisions can be formulated. Firstly, it might be the case that some apparent positivity biases are in fact negativity biases, if they are informationally mediated on the lines set out by Berlyne (1971). This argument would not necessarily act to reverse the negativity effect as well, since most of the relevant evidence reviewed by Peeters and Czapinski refers to strength rather than distribution functions; therefore, it would weaken instead the bidirectional structure of their model. Secondly, it might be the case that some positivity biases are maintained as such, if they are not informationally mediated but derive from some other mechanism. This would retain bi-directionality, but would render the model very diffuse since disparate mechanisms would have to be postulated. Thirdly, informational positivity biases might be operative, i.e. apparent negativity effects which, however, (being driven by the mechanism defined by Berlyne) act psychologically in the opposite direction to maximize the information contained in positive responses. This would support in general terms the position set out by Peeters and Czapinski, but in mirror-image form: a situation which necessarily results from observing biases in terms of response frequency, but inferring an underlying informational mechanism which emphasizes the minor pole of the operative dichotomy.

The present study addressed this directionality issue, but in addition the psychological nature of the hypothetical informational mechanism was investigated. In an earlier study the specific form of asymmetry predicted by Berlyne’s (1971) model was found in partialled favourability ratings, but not in partialled familiarity ratings (Tuohy, 1987). Following Moreland and Zajonc (1982) these two response criteria were assumed to be ‘hot’ (i.e. relatively affect-specific) and ‘cold’ (non-specific) respectively, and the fact that the predicted bias was restricted to favourability was discussed in terms of a new hypothesis: that the informational mechanism is relatively auton-

486 A . P. TuohyandS. G. Stradling

omous and affect-specific, perhaps on the lines suggested by Zajonc (1980). In suggest- ing that affect and cognition constitute two separate subsystems, Zajonc pointed out that a rapid, automatic and presumably adaptive mechanism is required if affect is to be thought of as primary, or as independent from cognition in any non-trivial sense. The tendency to assess the environment in just such a way is characteristic of informationally-mediated asymmetry on a putatively basic positive-negative dimension.

A procedure was devised which would test these hypotheses, and which would also address another issue previously raised: Tuohy and Stradling (1987) pointed out that these frequency/informational reversals may give rise to biases which are covertly operative within existing data-sets collected for quite other purposes, including normative data which may be used in a number of experimental contexts. This issue merits investigation on two main grounds. Firstly, any source of systematic bias, driven by subject or stimulus characteristics and unrecognized by researchers, may account for a significant proportion of the variance and thus may constitute a confounding variable. Secondly, the detection and investigation of such effects may provide insight into more fundamental psychological processes, such as the mediation of affect (Zajonc, 1980). Accordingly, in the present study sections of a large-scale, widely-used source of verbal norms (Toglia, Battig, Barrow, Cartwright, Posnansky, Pellegrino, Moore and Camilli, 1978) were examined for evidence of systematic positive-negative response asymmetries which might be covertly operative within this standard data-base; and it was hypothesized that those asymmetries mediated via favourability judgments would conform to Berlyne’s (197 1) informational index (enhancing the salience of the negative pole), while those mediated via familiarity judgements would not.

METHOD AND RESULTS

Toglia et al. (1978) compiled normative data for a total of 2854 English words, using 7-point rating scales on seven verbal dimensions: familiarity (FAM), pleasingness (PLS), meaningfulness (MNG), concreteness (CON), imagery (IMG), number of attributes (NOA), and categorizability (CAT). A total of 2500 subjects each rated 480 words on a single dimension: each word’s value on each dimension therefore represents the mean of about 60 responses. A data-base of 600 words (21 per cent) was extracted from this full list, comprising three samples of 200 trait adjectives, 200 nouns, and 200 verbs respectively. Within these categorical subsets the selection of items was made at random. The sample means for each of the seven verbal dimensions are shown in Table 1.

Table 1. Means and S.D.s for the trait, noun and verb samples on the seven verbal dimensions

FAM PLS MNG CON IMG NOA CAT

Traits Mean 5.86 3.87 4.43 3.35 4.12 3.55 3.66 S. D. 0.55 1.13 0.58 0.55 0.66 0.45 0.57

Nouns Mean 5.67 3.99 4.14 5.05 5.03 3.71 4.89 S. D. 0.81 0.75 0.69 1.07 0.92 0.64 1.02

Verbs Mean 5.79 3.92 4.10 3.54 4.02 3.45 3.55 S. D. 0.75 0.94 0.68 0.59 0.73 0.52 0.61


The intercorrelations of the seven dimensions are shown in Table 2 for the trait sample, together with their correlations as reported by Toglia et al. for the entire list of 2854 words. The intercorrelations for the noun and verb samples are shown in Table 3.

Table 2. Correlations between pairs of dimensions for 200 traits (bottom half of the table), and for the entire list of 2854 words (after Toglia et al., 1978, Table 1) (top half)


FAM 0.267 0.820 0.319 0.557 0.554 0.488 PLS 0.229 0.309 0.215 0.267 0.390 0.278 MNG 0.709 0.162 0.425 0.675 0.749 0.589 CON 0.216 0.003 0.190 0.883 0.386 0.887 IMG 0.341 0.065 0.559 0.649 0.543 0.905 NOA 0.392 0.333 0.602 0.125 0.360 0.524 CAT 0.477 0.053 0.564 0.630 0.785 0.315

Table 3. Correlations between pairs of dimensions for 200 nouns (bottom half of the table) and for 200 verbs (top half)


FAM 0.346 0.750 0.179 0.389 0.473 0.367 PLS 0.234 0.167 0.093 0.075 0.385 0.159 MNG 0.811 0.309 0.311 0.595 0.687 0.540 CON 0.388 0.097 0.297 0.766 0.286 0.776 IMG 0.586 0.171 0.514 0.890 0.427 0.832 NOA 0.500 0.372 0.692 0.015 0.216 0.489 CAT 0.527 0.227 0.477 0.836 0.884 0.230

The same analytical procedure was followed for each of the three separate samples. Toglia rt al. (1978) pointed out that ‘dimensional differences in overall means and standard deviations are sufficiently large to preclude any direct cross-dimensional comparisons in terms of the actual word rating values’ (p. 12). Accordingly, each of the seven sets of values was standardized within each of the three separate samples. For each word, the mean of its seven z-scores was then computed (MNZ). Each of the three samples was then sorted into an invariant order defined by this vector of cross-dimensional means.

Since MNZ represented a composite score to which each of the seven verbal dimensions contributed with equal weighting, it was assumed that it provided an index of the general positivity-negativity dimension discussed above. This assumption was tested as follows. Toglia et al. carried out a cluster analysis of the 2854 words on all seven dimensions, and reported eight distinct clusters. For the present 600 words, membership of these clusters was dummy-coded into seven binary vectors, on which MNZ was regressed. R2 was found to be 0.784 ( F = 306.072, df = 7,592, p < O.OOOl), thus indicating that close to 80 per cent of the variance in the eight-cluster structure was shared with MNZ.

488 A . P. Tuohy and S. G. Stradling

With the words within each sample now ordered along MNZ, a range of different levels of positive-negative dichotomization could be applied. For example, if the 100 items scoring lowest on MNZ were assigned a negative valence then a symmetrical differentiation would result, in which the probability of a negative item (PN) would be 0.50. By contrast, if only the lowest 40 items were assigned a negative valence then a highly asymmetrical differentiation would result, in which PN would be 0.20. For each sample, a systematic series of 19 such dichotomizations was encoded into 19 binary vectors, in which the 200 items (ordered on MNZ) were assigned PN values of 0.05, 0.10, 0. I5 . . . 0.95 by varying the cut-off point between positive and negative accordingly.

This primary manipulation allowed for the partialled relationships between FAM and PN, and PLS and PN, to be examined when the dichotomization was asymmetri- cally skewed to any extent and in either direction. One implication of Peeters and Czapinski’s work is that hypothetical within-subject tendencies can vary the degree and direction of asymmetry in accordance with various priorities: for example, modi- fying a negativity bias in response to the adaptive need for denial and repression (Benjafield, 1984); and it has been proposed that this variability can also be manipu- lated by outside influences, such as by psychotherapy (Schwartz and Garamoni, 1986, 1989). This analysis sought to model such tendencies by examining the relationship between PN (which indexed the amount of positive-negative asymmetry) and FAM, and between PN and PLS, for the separate trait, noun and verb samples. For each sample, these relationships were systematically measured by higher-order partial correlations, which held constant the effects of the other six verbal dimensions in each case.

Table 4. Standardized partial correlation coefficients for binary vectors at each level of PN with FAM (holding PLS, MNG, CON, IMG, NOA and CAT constant), and with PLS (holding FAM, MNG, CON, IMG, NOA and CAT constant), for the trait, noun and verb samples

zFAM ZPLS PN PN log, l/PN Traits Nouns Verbs Traits Nouns Verbs

0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95

0.216 0.332 0.41 1 0.464 0.500 0.521 0.530 0.529 0.518 0.500 0.474 0.442 0.404 0.360 0.31 1 0.258 0.199 0.137 0.070

-0.031 -0.041 -0.031 -0.039 -0.013

0.061 0.152 0.194 0.194 0.162 0.198 0.262 0.241 0.250 0.301 0.228 0.206 0.231 0.208

-0.130 -0.206 -0.191 -0.164 -0.182 -0.112 -0.099 -0.070

0.007 0.030 0.082 0.070 0.050 0.091 0.182 0.143 0.231 0.217 0.326

-0.039 -0.049 -0.064 -0.077 -0.043 -0.126 -0.132 -0.100 -0.035

0.056 0.082 0.059 0.072 0.083 0.111 0.105 0.280 0.402 0.552

0.049 0.175 0.182 0.278 0.301 0.440 0.455 0.477 0.370 0.301 0.247 0.290 0.266 0.180 0.185 0.150 0.145 0.031

-0.114

0.168 0.194 0.375 0.259 0.328 0.334 0.342 0.337 0.409 0.323 0.371 0.440 0.307 0.370 0.339 0.319 0.293 0.281 0.249 0.243 0.255 0.302 0.321 0.324 0.301 0.222 0.221 0.170 0.083 0.119 0.100 0.014 0.063 -0.025

-0.015 -0.1 11 -0.014 -0.095


These standardized partial correlations are shown in Table 4 for each level of PN, where it can be seen that the orthogonal relationships between the verbal dimensions and the underlying positive-negative polarization varied considerably with the degree of asymmetry indexed by PN. The point of interest was to determine whether significant linear or curvilinear trends existed within that variation, which might implicate particular forms of positive-negative asymmetry with particular stimulus properties. A series of regression analyses was carried out using the data in Table 4, treating the standardized partial correlation coefficients for FAM and PLS (labelled zFAM and zPLS respectively) in turn as the dependent variables, with PN and its transformation PNlog, liPN (i.e. its contribution to average uncertainty) as the independent variables. A series of highly specific hypotheses was tested in this way.

Hypothesis 1

It was predicted that all three zPLS indices (trait, noun and verb) would vary as asymmetrical inverted-U-shaped functions of PN, with maximal values associated with values of PN lower than 0.50 (i.e. that the zPLS function is maximized when there is a preponderance of positive stimuli). Three polynomial regressions were carried out and three similar, highly significant quadratic functions were observed for all the zPLS indices (see Figure 1). The results of these analyses are shown in Table 5, where it can be seen that Hypothesis 1 was strongly supported. It was concluded that, for all three classes of word, the unique relationship of the PLS dimension to the general positive-negative differentiation is greatest when PN is moderately low, i.e. when positive items are relatively over-represented in the stimulus field.

Table 5. Curvilinear regression of trait zPLS, noun zPLS, and verb zPLS on PN

R2 S. E. P (lin) P (quad) F (2,161 P Trait zPLS 0.839 0.064 2.930 -3.443 41.538 <0.0001

Verb zPLS 0.928 0.046 1.606 -2.445 103.633 <0.0001 Noun zPLS 0.855 0.054 1.340 -2.171 47.315 <0.0001

Hypothesis 2

If these asymmetrical effects reflect the consistent psychological tendency to organize negatively-rated events towards maximal salience, as suggested by Berlyne’s (1 97 1) informational model, then all three zPLS parameters should vary as significant positive linear functions of PNlog, 1/PN. Regression analyses showed that this was indeed the case (see Figure 2), and the results are shown in Table 6. The three regression coefficients were not significantly different from one another ( F = 0.2255, d f = 2, 51, ns), supporting the hypothesis that all three relationships were driven by the same tendency. It was concluded that, for all three classes of word, the unique relationship of the PLS dimension to the general positive-negative differentiation is greatest when PNlog, l/PN is maximized, i.e. when negative items are optimally differentiated from the stimulus field.

490 A . P. TuohyandS. G. Stradling

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Table 6. Linear regresson of trait zPLS, noun zPLS, and verb zPLS on PN log, 1/PN

r2 S. E. B F(1 . 17) 4

Trait zPLS 0.867 0.056 0.931 1 1 1.199 < 0.0001 Noun zPLS 0.746 0.069 0.864 49.852 < 0.0001 Verb zPLS 0.824 0.069 0.908 79.858 < 0.0001

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Hypothesis 3

If the informational negativity bias is specific to affectively-loaded judgments as previously argued (Tuohy, 1987), then the behaviour of the three zFAM parameters should differ from that of the three zPLS parameters. It was predicted that trait zFAM, noun zFAM and verb zFAM would yield functions of PN with profiles differing from those in Figure 1; as can be seen in Figure 3, three dissimilar functions were obtained, highly significant (see Table 7) but asymmetrical in the opposite direction. Hypothesis 3 was therefore supported, and it was concluded that, for all three classes of word, the unique relationship of the FAM dimension to the general positive-negative differentiation is enhanced when PN is high, i.e. when negative items are relatively over-represented in the stimulus field.

Table 7. Curvilinear regression of trait zFAM, noun zFAM, and verb zFAM on PN

R2 S. E. P (W P (quad) F ( 2 , 16) P

Trait zFAM 0.890 0.041 2.425 -1.608 65.016 <0.0001 Noun zFAM 0.949 0.038 0.509 0.472 148.891 <0.0001 Verb zFAM 0.903 0.060 -1.104 1.986 14.676 <0.0001

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Figure 3. Curvilinear regression of the zFAM data on PN

Hypothesis 4

Since the trait, noun and verb zFAM parameters were highly significant inverted-U- shaped functions of PN, but asymmetrical in the opposite direction from the three zPLS parameters, it was hypothesized that they might be modelled by the transformation (1-PN)log, l/(l-PN), which would reflect a tendency to enhance the salience of the positive response set rather than the negative. The three linear functions are shown in Figure 4, and it can be seen from Table 8 that trait zFAM was positively


related to (1-PN)log, lI(1-PN) as hypothesized. However, noun zFAM and verb zFAM showed no significant relationship with (1-PN)log, U(1-PN). A test for the homogeneity of the regression coefficients in Table 8 showed that these three slopes differed significantly from each other ( F = 11.830, df= 2,51, p < 0.001). Since these results lacked the statistical identity of the three zPLS functions, no single explanatory mechanism was indicated. However, the trait zFAM effect was consistent with a positivity bias, informationally operative but in the opposite direction to the three zPLS effects, as predicted.

Table 8. Linear regression of trait zFAM, noun zFAM, and verb zFAM on (I-PN) log, 1/( 1 -PN)

r2 S. E. B F(1, 17) P Trait zFAM 0.638 0.073 0.799 30.023 < 0.0001 Noun zFAM 0.183 0.149 0.427 3.798 ns Verb zFAM 0.001 0.186 0.023 0.009 ns

TTrait zFAM DNoun rF AM @Verb zFam .6

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Figure 4. Linear regression of the zFAM data on (1 -PN) log, 1 /( 1 -PN)

DISCUSSION

The complex procedure reported here utilized a matrix of standardized partial correlation coefficients (Table 4) as data for a higher-order analysis which requires careful interpretation. The results demonstrated that, for these three classes of semantic stimuli, the orthogonal contribution of pleasingness to the positive-negative dimension consistently varies as an inverted-U-shaped function of the amount of asymmetry introduced into the latter; and is maximized when the informational content (weighted by probability) of the negative pole is also maximized. This effect is supportive of findings earlier reported (Benjafield, 1985; Tuohy, 1987), and also supports the


suggestion that informationally-mediated asymmetry effects are likely to be operative in normative data (Tuohy and Stradling, 1987).

For familiarity, the equivocal nature of the present results makes interpretation much more difficult. Nevertheless, where a significant fit is obtained (with the trait sample) to the same informational transformation, it is based on (1-PN), and hence associated with positivity rather than negativity. Reversing the effects adduced from pleasingness, it can be said that the orthogonal contribution of trait familiarity to the positive-negative dimension consistently varies as a function of the amount of asymmetry introduced into the latter; and is maximized when the informational content (weighted by probability) of the positive pole is also maximized. This effect does not hold for nouns and verbs, however.

This pattern of results has a number of implications. The differential effects of pleasingness and familiarity were predicted, as was the nature of the former (i.e. an informationally mediated negativity bias). However, evidence for a similar effect (but linked to positivity) associated with one of the familiarity samples suggests that pleasingness and familiarity may both be mediated via a tendency towards l/e (the probability level where contribution to average uncertainty is maximized). If only the direction of asymmetry, and not its extent, differs across the pleasingness/ familiarity dichotomy, some previous theoretical arguments may have to be modified. Tuohy (1987) used the partialled effects of favourability as an affective index of response, obtaining an asymmetrical bias tending to lle, as opposed to the partialled effects of familiarity ratings, which were symmetrical. These findings were discussed in terms of Zajonc’s (1980, 1984) hypothesis that affect and cognition are in a non- trivial sense separately mediated, and it was suggested that this asymmetrical tendency might well be an operating characteristic of the hypothetical affective mediator. In the light of the present results, which would suggest a similar informational mechanism underlying both pleasingness and some contexts of familiarity, the extent of that separation becomes more problematical.

On the other hand, these oppositional results are to some extent supportive of the bi-directional asymmetry model proposed by Peeters and Czapinski (1990), since they provide some evidence that both positivity and negativity effects may be placed on the same operational basis, here shown to be predicated on a tendency towards lle. This suggestion is weakened by the fact that two of the three verbal samples did not show a significant positive informational effect. In spite of this inconsistency, nevertheless, the present results may be said, provisionally at least, to favour the ‘mirror-image’ form of the bi-directional model: pleasingness relates most strongly to the primary positive-negative dimension when positives are more frequent and negatives are most complex, while familiarity (for some classes of stimuli) yields precisely the opposite effect. This argues that some positivity biases and some negativity biases are implicated with the same psychological mechanism, insofar as they exhibit the same operating characteristics, and differ only in directionality. However, the inconsistent effects of familiarity indicate that this question remains open. What- ever factors were operative here to distinguish the trait sample from the nouns and verbs on the familiarity index are unknown, but the orthogonal basis of the analyses suggests that they were not due to the effects of the other six verbal dimensions.

In relating these findings to established models of the affect-cognition relation, it may be noted that Scherer’s component process model of emotion (Scherer, 1984;


Leventhal and Scherer, 1987) modified the outright separatist position proposed by Zajonc (1980,1984), and distinguished between familiarity and pleasingness assess- ments in terms of the first and second of five separate ‘stimulus evaluation checks’ (SECs), which were proposed as characteristic of an organism’s interaction with the environment. Each of these SECs was considered to be implemented at different levels of processing complexity (see Table 9). Both the familiarity and pleasingness SECs would have to be very rapid and presumably automatic in their mode of processing: indeed, at the sensory-motor level Leventhal and Scherer (1987) linked them to the orienting and defence responses, respectively. In this respect, a ‘wired-in’, informational mediator is a suitable mechanism.

Table 9. Processing levels for Stimulus Evaluation Checks (after Leventhal and Scherer, 1987, Table 2 )

SEC 1 + SEC2 Level familiarity pleasingness

1. Sensory-motor Sudden, intense stimulation Innate preferences/aversions

2. Schematic Familiarity: schemata Learned preferences/aversions l

1 matching

Expectations: cause/effect, Recalled, anticipated or probability estimates derived positive-negative

3. Conceptual

evaluations

A speculative connection can be made, in which these early SECs provide a means of assessing the environment in such a way as to enhance the informational content of the familiar (thus expediting approach behaviours), and of the unpleasing elements (thus expediting avoidance behaviour), on the lines proposed by Peeters and Cza- pinski. Presumably the ratings reported by Toglia et al. reflect operations carried out at the schematic or conceptual levels defined by Leventhal and Scherer; it can be suggested, however, that the effects of an early informational tendency may con- tinue to reverberate through higher levels and later stages of this hypothetical SEC process. Such an on-going reverberation, although normally over-written by later processing characteristics, would give the informational mechanism the status of a ‘weak background force’ (Stradling, Tuohy and Harper, 1990), and would account for the covert nature of its effects in normative data.

A further 79 per cent of the full word list provided by Toglia et al. remains to be examined. Even for the present samples, the role of the other five verbal dimensions may give rise to a further range of hypotheses, some of which may provide tests for the present conclusions. For example, the partialled effects of imagery and concreteness could be studied on the grounds that these two dimensions ought to yield results similar to the pleasingness effects detailed here. Paivio (Paivio and Begg, 198 1; Paivio, Yuille and Madigan, 1968) considered that imagery and concreteness dimensions access the same underlying process, though implicated with separate hypothetical imagery and verbal systems; and that pleasingness may also be connected to imaginal processes (Benjafield, 1987; Paivio, 1978). It is clear that the complexities of the very rich data-base have only begun to be explored.


ACKNOWLEDGEMENTS

The authors thank Amanda Bell, David Bell, and Vicky Houston for their help in organizing the data.

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