The Obama effect: Decreasing implicit prejudice and stereotyping

This project explores the impact of Barack Obama’s presidential campaign and the resulting high levels of exposure to a positive, counter-stereotypic Black exemplar, on prejudice and stereotyping among non-Black participants. We found dramatically decreased levels of implicit anti-Black prejudice and stereotyping as compared with bias observed previously at the same institutions and in the literature. Providing some insight why the bias was reduced, Study 1 demonstrated that participants had positive Black exemplars come to mind or anticipated that other people have positive exemplars come to mind when they thought of Black people and this was associated with low levels of racial prejudice. Our second study revealed that participants who had qualities strongly associated with Obama as a political figure (e.g., president) activated when they were primed with “Black” had lower levels of implicit prejudice. These findings indicate that the extensive exposure to Obama resulted in a drop in implicit bias.     

THE GENDER STEREOTYPING OF EMOTIONS

Three studies documented the gender stereotypes of emotions and the relationship between gender stereotypes and the interpretation of emotionally expressive behavior. Participants believed women experienced and expressed the majority of the 19 emotions studied (e.g., sadness, fear, sympathy) more often than men. Exceptions included anger and pride, which were thought to be experienced and expressed more often by men. In Study 2, participants interpreted photographs of adults'ambiguous anger/sadness facial expressions in a stereotype-consistent manner, such that women were rated as sadder and less angry than men. Even unambiguous anger poses by women were rated as a mixture of anger and sadness. Study 3 revealed that when expectant parents interpreted an infant's ambiguous anger/sadness expression presented on videotape only high-stereotyped men interpreted the expression in a stereotype-consistent manner. Discussion focuses on the role of gender stereotypes in adults'interpretations of emotional expressions and the implications for social relations and the socialization of emotion.     

Perfectionism,Shame, and Depressive Symptoms

The authors examined the relationship between depression, maladaptive perfectionism, and shame. Regression analyses were used to replicate a model in which maladaptive perfectionism was negatively associated with self‐esteem and positively associated with symptoms of depression, with self‐esteem mediating the effects of maladaptive perfectionism on depressive symptoms. Additional models showed that the path from maladaptive perfectionism to depression was partially mediated by shame, although these paths differed for men and women.     

The Neurodynamics of Cognition: A Tutorial on Computational Cognitive Neuroscience

Computational Cognitive Neuroscience (CCN) is a new field that lies at the intersection of computational neuroscience, machine learning, and neural network theory (i.e., connectionism). The ideal CCN model should not make any assumptions that are known to contradict the current neuroscience literature and at the same time provide good accounts of behavior and at least some neuroscience data (e.g., single-neuron activity, fMRI data). Furthermore, once set, the architecture of the CCN network and the models of each individual unit should remain fixed throughout all applications. Because of the greater weight they place on biological accuracy, CCN models differ substantially from traditional neural network models in how each individual unit is modeled, how learning is modeled, and how behavior is generated from the network. A variety of CCN solutions to these three problems are described. A real example of this approach is described, and some advantages and limitations of the CCN approach are discussed.     

Procedural learning of unstructured categories

Unstructured categories are those in which the stimuli are assigned to each contrasting category randomly, and thus there is no rule- or similarity-based strategy for determining category membership. Intuition suggests that unstructured categories are likely to be learned via explicit memorization that is under the control of declarative memory. In contrast to this prediction, neuroimaging studies of unstructured-category learning have reported task-related activation in the striatum, but typically not in the hippocampus—results that seem more consistent with procedural learning than with a declarative-memory strategy. This article reports the first known behavioral test of whether unstructured-category learning is mediated by explicit strategies or by procedural learning. Our results suggest that the feedback-based learning of unstructured categories is mediated by procedural memory.     

Religious Coping,Coping Resources,and Depressive Symptoms: Test of a Mediation Model

This study examined the relationships between religious coping, coping resources, and depressive symptoms. The authors tested whether coping resources explained the link between religious coping and depressive symptoms in a sample of 349 college students. Results indicated that coping resources partially mediated the relationship between negative religious coping and depressive symptoms, primarily through decreased social ease. The results offered no evidence that coping resources mediated the relationship between positive religious coping and depressive symptoms.     

Responses to interracial interactions over time

The current work tested and expanded on Plant and Devine's (2003) model of the antecedents and implications of interracial anxiety by examining people's experiences with interracial interactions at two time points. Study 1 explored non-Black people's responses to interactions with Black people and Study 2 explored Black people's responses to interactions with White people. Non-Black participants' expectancies about coming across as biased in interracial interactions and Black participants' expectancies about White people's bias predicted their interracial anxiety and whether they had positive interactions with outgroup members during the 2 weeks between assessments. Across both studies, interracial anxiety predicted the desire to avoid interactions with outgroup members. In addition, participants who were personally motivated to respond without prejudice reported more positive expectancies. The findings are discussed in terms of the implications for understanding the course and quality of interracial interactions.     

The regulation of explicit and implicit race bias: the role of motivations to respond without prejudice

Three studies examined the moderating role of motivations to respond without prejudice (e.g., internal and external) in expressions of explicit and implicit race bias. In all studies, participants reported their explicit attitudes toward Blacks. Implicit measures consisted of a sequential priming task (Study 1) and the Implicit Association Test (Studies 2 and 3). Study 3 used a cognitive busyness manipulation to preclude effects of controlled processing on implicit responses. In each study, explicit race bias was moderated by internal motivation to respond without prejudice, whereas implicit race bias was moderated by the interaction of internal and external motivation to respond without prejudice. Specifically, high internal, low external participants exhibited lower levels of implicit race bias than did all other participants. Implications for the development of effective self-regulation of race bias are discussed.     

What makes a categorization task difficult?

To understand why some categorization tasks are more difficult than others, we consider five factors that may affect human performance--namely, covariance complexity, optimal accuracy level with and without internal noise, orientation of the optimal categorization rule, and class separability. We argue that covariance complexity, an information-theoretic measure of complexity, is an excellent predictor of task difficulty. We present an experiment that consists of five conditions using a simulated medical decision-making task In the task human observers view hundreds of hypothetical patient profiles and classify each profile into Disease Category A or B. Each profile is a continuous-valued, three-dimensional stimulus consisting of three vertical bars, where each bar height represents the result of a medical test. Across the five conditions, covariance complexity was systematically manipulated. Results indicate that variation in performance is largely a function of covariance complexity and partly a function of internal noise. The remaining three factors do not explain performance results. We present a challenge to categorization theorists to design models that account for human performance as predicted by covariance complexity.