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      Visualizing Gendered Representations of Male and Female Teachers Using a Reverse Correlation Paradigm

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          Abstract. Stereotypically, men are expected to outperform women in science, technology, engineering, and mathematics (STEM) domains, and women to outperform men in language. We conceptually replicated this association using reverse correlation tasks. Without available gender information, participants generated male images of physics teachers and female images of language teachers (Studies 1 and 3). Personal endorsement of respective ability stereotypes inconsistently predicted these effects (Studies 1 and 3). With unambiguous gender information (Study 2), participants generated feminized images of female language teachers and masculinized images of female physics teachers, whereas images of male teachers were unaffected by academic domain. Stereotype endorsement affected perceptions of female but not male teachers, suggesting that appearing feminine in STEM domains still signals professional mismatch.

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          Most cited references 39

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          Associative and propositional processes in evaluation: an integrative review of implicit and explicit attitude change.

          A central theme in recent research on attitudes is the distinction between deliberate, "explicit" attitudes and automatic, "implicit" attitudes. The present article provides an integrative review of the available evidence on implicit and explicit attitude change that is guided by a distinction between associative and propositional processes. Whereas associative processes are characterized by mere activation independent of subjective truth or falsity, propositional reasoning is concerned with the validation of evaluations and beliefs. The proposed associative-propositional evaluation (APE) model makes specific assumptions about the mutual interplay of the 2 processes, implying several mechanisms that lead to symmetric or asymmetric changes in implicit and explicit attitudes. The model integrates a broad range of empirical evidence and implies several new predictions for implicit and explicit attitude change.
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            Sexism and racism: Old-fashioned and modern prejudices.

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              Understanding current causes of women's underrepresentation in science.

               S Ceci,  W M Williams (2011)
              Explanations for women's underrepresentation in math-intensive fields of science often focus on sex discrimination in grant and manuscript reviewing, interviewing, and hiring. Claims that women scientists suffer discrimination in these arenas rest on a set of studies undergirding policies and programs aimed at remediation. More recent and robust empiricism, however, fails to support assertions of discrimination in these domains. To better understand women's underrepresentation in math-intensive fields and its causes, we reprise claims of discrimination and their evidentiary bases. Based on a review of the past 20 y of data, we suggest that some of these claims are no longer valid and, if uncritically accepted as current causes of women's lack of progress, can delay or prevent understanding of contemporary determinants of women's underrepresentation. We conclude that differential gendered outcomes in the real world result from differences in resources attributable to choices, whether free or constrained, and that such choices could be influenced and better informed through education if resources were so directed. Thus, the ongoing focus on sex discrimination in reviewing, interviewing, and hiring represents costly, misplaced effort: Society is engaged in the present in solving problems of the past, rather than in addressing meaningful limitations deterring women's participation in science, technology, engineering, and mathematics careers today. Addressing today's causes of underrepresentation requires focusing on education and policy changes that will make institutions responsive to differing biological realities of the sexes. Finally, we suggest potential avenues of intervention to increase gender fairness that accord with current, as opposed to historical, findings.

                Author and article information

                Social Psychology
                Hogrefe Publishing
                July 1, 2019
                : 50
                : 4
                : 233-251
                [ 1 ]Department of Social Psychology, Universität Hamburg, Germany
                [ 2 ]Department of Education, Leibniz Universität Hannover, Germany
                Author notes
                Juliane Degner, Department of Social Psychology, Universität Hamburg, Von-Melle-Park 5, 20146 Hamburg, Germany, E-mail juliane.degner@ 123456uni-hamburg.de
                Self URI (journal-page): https://econtent.hogrefe.com/loi/zsp
                Original Article


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