This study investigated the effects and interplay of several core determinants of consensus in person perception: information overlap, information quantity, cross-situational consistency, and shared meaning. Targets (
Most psychological theories are expressed in natural language terms, which incurs a number of important problems (e.g., vagueness, limited refutability, lack of parsimony, possible contradictiveness, redundancy and specification gaps). Better theory specification has been called for many times, and formalization is a means of achieving it. We present a formal account of “valence asymmetry”, that is: the notion that positive and negative stimuli affect information processing differentially. Most often, negative stimuli are assumed to have a stronger impact (“negativity bias”). We formalize two of the major frameworks that have been offered as explanations for this alleged asymmetry: The first framework emphasizes the role of valence as a trigger for deeper information processing. It posits that negative stimuli are more survival-relevant than positive ones. The second framework emphasizes the relative similarity and frequency of stimuli. Here, it is assumed that negative stimuli are less similar to one another and less frequent, and therefore afford greater processing effort. Valence itself does not affect information processing within this framework. Our formal analysis highlights the conceptual complexity of these issues, which remains hidden when using the traditional narrative form. For example, we explicate several implicit assumptions that are necessary to arrive at some of the major predictions about valence asymmetry. Both frameworks may be expressed using a single set of parameters, with considerable (but not perfect) overlap. Formalizing valence asymmetry explanations is clearly advantageous in terms of exactness, parsimony, and comparative testability.
Patterns of correlations among judgments of targets on different items are the basis for common psychometric procedures such as factor analysis and network modeling. The outcomes of such analyses may shape the images (i.e., theories) that we as scientists have of the phenomena that we study. However, key conceptual issues tend to be overlooked in these analyses, which is especially problematic when the items are person descriptions espressed in the natural language. A correlation between judgments on two such items may reflect the influences of (a) a common substantive cause, (b) substantive target characteristics on another, (c) semantic redundancy, (d) the perceivers’ attitudes toward the targets, (e) the perceivers’ formal response styles, or (f) any mixture of these. We present a conceptual framework integrating all of these mechanisms and use it to connect formerly unrelated strands of theorizing with one another. A lack of awareness regarding the complexity involved may compromise the validity of interpretations of psychometric analyses. We also review the effectiveness of a broad range of solutions that have been proposed for dealing with the various influences, and provide recommendations for future research.
Abstract. In this exploratory study, a group of subjects was asked to come up with visible and quantifiable behaviors tied to certain person-descriptive adjectives. Another group of subjects then rated how much different levels of the behaviors would justify the use of each adjective to describe a person, as a cross-validation. The reliability of these ratings was excellent. Associations between adjectives and “their” behaviors were very strong and largely specific. The shapes of associations were usually linear or negatively accelerated, which is highly relevant for the formal modeling of person perception processes. Researchers aiming to measure personality in terms of behavior should make more systematic use of the knowledge that competent users of the natural language already share in this regard.
Serial judgments of different target persons in a given situation can depend on the target’s position in the series: Perceivers may initially withhold extreme judgments to avoid violating their judgment algorithm’s consistency in case of more extreme observations later on. With subsequent observations, perceivers may better calibrate their judgment scale. We extend this theoretical reasoning on calibration effects to personality inferences: Between-target rating variability, consensus, and accuracy may be diminished in initial judgments if perceivers prefer moderate judgments regardless of the target. We tested and cross-validated these preregistered expectations using a sample of 3,963 perceivers who judged 200 targets regarding their personalities in 20 different situations. Whereas rating variability and consensus increased across the judgment series, accuracy did not. However, initial judgments were not always more moderate (e.g., higher Agreeableness) suggesting that perceivers reference trait-specific default values. This may be beneficial or detrimental for targets, depending on how their actual characteristics compare.
First impressions are commonly assumed to be particularly important: Information about a person that we obtain early on may shape our overall impression of that person more strongly than information obtained later. In contrast to previous research, the present series of preregistered analyses uses actual person judgment data to investigate this so-called primacy effect: Perceivers ( N = 1,395) judged the videotaped behavior of target persons ( N = 200) in 10 different situations. Separate subsamples of about 200 perceivers each were used in moving from exploratory to increasingly confirmatory analyses. Contrary to our expectations, no primacy effect was found. Instead, judgments of the targets in later situations were more strongly associated with overall impressions, indicating an acquaintance effect. Relying on early information seems unreasonable when more comprehensive information is readily available. Early information may, however, affect perceivers’ behavioral reactions to the targets and thus their future interactions, if such interactions are possible.
Personality self- and informant-reports have been ascribed complementary value based on the asymmetric knowledge of the two perspectives. However, this study is the first to investigate what personality (item) content is reflected in the shared and unique components in multi-rater personality judgments. In two large data sets (Sample 1: 664 targets/1,615 informants; Sample 2: 478 targets/1,434 informants), we used latent variable models to separate judgments into variance that is shared across targets and informants (the Trait factor), unique to self-reports (Identity), and unique to informant-reports (Reputation). Then, we predicted the personality items’ loadings for each factor from the items’ content. This included items’ affective, behavioral, cognitive, or desire-related content, observability and evaluativeness, and centrality to identity or reputation. We found that Trait consensus was generally promoted by items reflecting observable, behavioral, but also affective content. Unique self-perceptions were captured especially by cognitions and non-observable content. Evaluativeness had inconsistent effects across samples. Similarly, unique informant-views reflected different content across samples. Both may depend on the types of informants or the available item sample. These insights build the foundation for leveraging the power of multi-rater perspectives on personality for advancing theory and measurement across different perspectives.
Person judgments reflect perceiver effects: differences in how perceivers judge the average person. The factorial structure of such effects is still discussed. We present a large-scale, preregistered replication study using over 1 million person judgments (different groups of 200 perceivers judged 200 targets in one of 20 situations, using 30 personality items). Results unanimously favored a model comprising three systematic components: acquiescence (endorsing all items more than other perceivers), positivity (endorsing positive over negative items), and trait specificity (endorsing items reflecting a specific trait more). The latter two factors each accounted for approximately a quarter of the variance in perceiver effects, and acquiescence accounted for less than 10%. Positivity was more influential for evaluative items and was strongly associated with how likable perceivers found their targets to be ( r = .55). With considerable statistical power and generalizability, our findings significantly improve the knowledge base regarding the structure of perceiver effects.
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