Forming impressions from stereotypes, traits, and behaviors: A parallel-constraint-satisfaction theory.

Abstract

The authors propose a parallel-constraint-satisfaction theory of impression formation that assumes that social stereotypes and individuating information such as traits or behaviors constrain each other's meaning and jointly influence impressions of individuals. Building on models of text comprehension (W. Kintsch, 1988), the authors describe a connectionist model that can account for the major findings on how stereotypes affect impressions of individuals in the presence of different kinds of individuating information; how stereotypes, behaviors, and traits affect each other's meaning; and how multiple stereotypes jointly affect impressions. Most of these findings can be modeled by constraint networks, which suggests that they may be due to relatively automatic processes that require little conscious inference. The authors also point to a small number of phenomena that involve more controlled processes. The advantages of the authors' parallel model over serial models are discussed.How friendly is the person you have just met at the party? How aggressive is your neighbor? How decisive is President Clinton? Your answers to such questions may be shaped by your understanding of the implications of these people's behavior, profession, age, sex, ethnicity, interpersonal relations, personality traits, physical appearance, abilities, goals, family background, or any other information about them that you consider relevant. These diverse varieties of information that can shape our impressions of others are typically classified by social psychologists into two major kinds-stereotypes and individuating information (Brewer, 1988;Fiske & Neuberg, 1990;Locksley, Hepburn, & Ortiz, 1982). Stereotypes refer to membership in social categories such as sex, race, age, or profession that are believed to be associated with certain traits and behaviors. Individuating information refers to anything else known about the individual-behavior (e.g., hit someone), personality (e.g., introverted), family circumstances (e.g., has two brothers), etc. As we shall discuss later, the distinction between these two kinds of information is not always clear. But many theorists have treated them as qualitatively different, and a great deal of theoretical and empirical effort has gone into determining how an

Modeling Option and Strategy Choices with Connectionist Networks: Towards an Integrative Model of Automatic and Deliberate Decision Making

“…An iterative updating algorithm can be used to simulate consistency maximizing by spreading activation. Such parallel constraint satisfaction (PCS) network models have been successfully applied to explain processes of letter and word perception (McClelland & Rumelhart, 1981), social perception (Read & Miller, 1998), analogical mapping (Holyoak & Thagard, 1989), the evaluation of explanations (Thagard, 1989), dissonance reduction (Shultz & Lepper, 1996), impression formation (Kunda & Thagard, 1996), the selection of plans (Thagard & Millgram, 1995), legal decision making (Holyoak & Simon, 1999;Simon, 2004), preferential choice and probabilistic decisions (Glöckner, 2006;Glöckner, 2007;.…”

Labeling Bias and Categorical Induction: Generative Aspects of Category Information.

“…For example, the strength of a conclusion Linda majored in philosophy in college given a premise Linda is a feminist can be judged by evaluating feature vectors associated with the two predicates (see Osherson, Smith, Shafir, Gualtierotti, & Biolsi, 1995 Sloman's (1993) model (but see also Sloman, 1994Sloman, , 1997, for another approach to evaluate predicate induction). 4 There are several other models that have been developed in social cognition research (Kunda & Thagard, 1996; E. R. Smith & Zarate, 1992). These models are essentially analogous to Sloman's (1993) model.…”

“…Main psychological accounts of inductive judgments suggest that two factors-(a) matching attributes between entities and (b) the coverage of premises over a conclusion (hereafter I call these two factors attribute-based similarity)-are the guiding forces of inferences (see Heit, 2000, for a review; Kunda & Thagard, 1996;Osherson, Smith, Wilkie, Lopez, & Shafir, 1990;Osherson, Stern, Wilke, Stob, & Smith, 1991;Rips, 1975;Sloman, 1993; E. R. Smith & Zarate, 1992;Tversky, 1977). According to this view, for example, the conclusion Lions have Disease X, given a premise, Zebras have Disease X, is credible proportional to the extent to which the two entities-zebras and lions-have features in common and the magnitude of an entity in a premise (i.e., zebras) exceeds that of a conclusion (lions; i.e., coverage).…”

“…In the field of judgment and decision making, researchers have also emphasized the dominance of similarity information (e.g., representative heuristics; Kahneman & Tversky, 1973;Tversky & Kahneman, 1983). The same focus has been prevalent in stereotyping and impression-formation research (Allport, 1954;Duckitt, 1992;Hamilton & Sherman, 1994;Kashima, Woolcock, & Kashima, 2000;Kunda & Thagard, 1996;Stangor, 2000).…”

Masculinity causes speeding in young men

“…Following a connectivism approach, priming one specific concept (e.g., masculinity) activates related concepts (e.g., risk behavior) which become easily accessible so that these concepts are able to affect our behavior (e.g., speeding) even without us noticing it (Kunda and Thagard, 1996). Our findings are thus in accordance with previous literature suggesting that the identification with or the activation of the traditional male gender role is a threat to a person's health (Courtenay, 2000;Lippa et al, 2000) and more specifically to driving fast.…”