People can make decisions to join a group based solely on exposure to that group's physical environment. Four studies demonstrate that the gender difference in interest in computer science is influenced by exposure to environments associated with computer scientists. In Study 1, simply changing the objects in a computer science classroom from those considered stereotypical of computer science (e.g., Star Trek poster, video games) to objects not considered stereotypical of computer science (e.g., nature poster, phone books) was sufficient to boost female undergraduates' interest in computer science to the level of their male peers. Further investigation revealed that the stereotypical broadcast a masculine stereotype that discouraged women's sense of ambient belonging and subsequent interest in the environment (Studies 2, 3, and 4) but had no similar effect on men (Studies 3, 4). This masculine stereotype prevented women's interest from developing even in environments entirely populated by other women (Study 2). Objects can thus come to broadcast stereotypes of a group, which in turn can deter people who do not identify with these stereotypes from joining that group.

Women obtain more than half of U.S. undergraduate degrees in biology, chemistry, and mathematics, yet they earn less than 20% of computer science, engineering, and physics undergraduate degrees (National Science Foundation, 2014a). Gender differences in interest in computer science, engineering, and physics appear even before college. Why are women represented in some science, technology, engineering, and mathematics (STEM) fields more than others? We conduct a critical review of the most commonly cited factors explaining gender disparities in STEM participation and investigate whether these factors explain differential gender participation across STEM fields. Math performance and discrimination influence who enters STEM, but there is little evidence to date that these factors explain why women's underrepresentation is relatively worse in some STEM fields. We introduce a model with three overarching factors to explain the larger gender gaps in participation in computer science, engineering, and physics than in biology, chemistry, and mathematics: (a) masculine cultures that signal a lower sense of belonging to women than men, (b) a lack of sufficient early experience with computer science, engineering, and physics, and (c) gender gaps in self-efficacy. Efforts to increase women's participation in computer science, engineering, and physics may benefit from changing masculine cultures and providing students with early experiences that signal equally to both girls and boys that they belong and can succeed in these fields. (PsycINFO Database Record

Theories of race relations have been shaped by the concept of a racial hierarchy along which Whites are the most advantaged and African Americans the most disadvantaged. However, the recent precipitated growth of Latinos and Asian Americans in the United States underscores the need for a framework that integrates more groups. The current work proposes that racial and ethnic minority groups are disadvantaged along 2 distinct dimensions of perceived and perceived, such that the 4 largest groups in the United States are located in 4 discrete quadrants: Whites are perceived and treated as superior and American; African Americans as inferior and relatively American compared with Latinos and Asian Americans; Latinos as inferior and foreign; and Asian Americans as foreign and relatively superior compared to African Americans and Latinos. Support for this Racial Position Model is first obtained from targets' perspectives. Different groups experience distinct patterns of racial prejudice that are predicted by their 2-dimensional group positions (Studies 1 and 2). From perceivers' perspectives, these group positions are reflected in the content of racial stereotypes (Study 3), and are well-known and consensually recognized (Study 4). Implications of this new model for studying contemporary race relations (e.g., prejudice, threat, and interminority dynamics) are discussed. (PsycINFO Database Record

Five studies investigate identity denial, the situation in which an individual is not recognized as a member of an important in-group. Asian Americans are seen as less American than other Americans (Study 1) and realize this is the case, although they do not report being any less American than White Americans (Studies 2A and 2B). Identity denial is a common occurrence in Asian Americans' daily lives (Study 3). They react to instances of identity denial by presenting American cultural knowledge and claiming greater participation in American practices (Studies 4 & 5). Identity denial furthers the understanding of group dynamics by capturing the experience of less prototypical group members who desire to have their common in-group identity recognized by fellow group members.

Despite having made significant inroads into many traditionally male-dominated fields (e.g., biology, chemistry), women continue to be underrepresented in computer science and engineering. We propose that students’ stereotypes about the culture of these fields—including the kind of people, the work involved, and the values of the field—steer girls away from choosing to enter them. Computer science and engineering are stereotyped in modern American culture as male-oriented fields that involve social isolation, an intense focus on machinery, and inborn brilliance. These stereotypes are compatible with qualities that are typically more valued in men than women in American culture. As a result, when computer science and engineering stereotypes are salient, girls report less interest in these fields than their male peers. However, altering these stereotypes—by broadening the representation of the people who do this work, the work itself, and the environments in which it occurs—significantly increases girls’ sense of belonging and interest in the field. Academic stereotypes thus serve as gatekeepers, driving girls away from certain fields and constraining their learning opportunities and career aspirations.