4.2 Article

Engineers and Engineeresses? Self-conceptions and the Development of Gendered Professional Identities

期刊

SOCIOLOGICAL PERSPECTIVES
卷 58, 期 1, 页码 56-77

出版社

SAGE PUBLICATIONS INC
DOI: 10.1177/0731121414556543

关键词

professional identity; self-conceptions; professional culture; gender inequality; engineering

资金

  1. National Science Foundation [0240817, 0241337, 0609628, 0503351]
  2. National Science Foundation Dissertation Improvement Grant [1029668]
  3. Direct For Social, Behav & Economic Scie [0609628] Funding Source: National Science Foundation
  4. Direct For Social, Behav & Economic Scie
  5. Divn Of Social and Economic Sciences [1029668] Funding Source: National Science Foundation
  6. Divn Of Social and Economic Sciences [0609628] Funding Source: National Science Foundation
  7. Divn Of Social and Economic Sciences
  8. Direct For Social, Behav & Economic Scie [0240817, 0503351, 0241337] Funding Source: National Science Foundation

向作者/读者索取更多资源

Do men and women in the same field develop different professional identities? This paper theoretically articulates and empirically explores a mechanism of such gendering: Self-conceptions may filter the identity traits emphasized by professional cultures so that only traits consistent with one's self-conceptions are likely to be adopted into one's professional identity. As such, systematic gender differences in self-conceptions may be relayed into gender variation in professional identities. Using longitudinal survey data of engineering students from four U.S. colleges, I find that four self-conceptions, two gendered and two gender-neutral, predict students' adoption of four professional identity traits: problem-solving prowess, technological leadership, managerial/communication skills, and social consciousness. Two of these traits are gendered: Women are less likely than men to value technological leadership but more likely to value social consciousness. Suggesting possible career consequences of professional identities, I find that three professional identity traits predict students' intentions to remain in engineering.

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