Gender differences in academic advancement: patterns, causes, and potential solutions in one US College of Medicine

Acad Med. 2003 May;78(5):500-8. doi: 10.1097/00001888-200305000-00015.

Abstract

Purpose: The influx of women into academic medicine has not been accompanied by equality for male and female faculty. Women earn less than men in comparable positions, progress more slowly through academic ranks, and have not attained important leadership roles. This study tested hypotheses about why gender disparities exist in salary, rank, track, leadership, and perceptions of campus climate at one academic center, the University of Arizona College of Medicine, Tucson.

Method: Salary, rank, and track data were obtained from institutional databases for the 1999-2000 fiscal year. A structured, online questionnaire was made available to 418 faculty members to collect information about their goals, attitudes, and experiences.

Results: A total of 198 faculty members completed the questionnaire. The data showed significant gender differences in faculty salaries, ranks, tracks, leadership positions, resources, and perceptions of academic climate. On average, women earned US dollars 12777 or 11% less than men, after adjusting for rank, track, degree, specialty, years in rank, and administrative positions (p <.0003). Of female faculty, 62% were assistant professors (49% of women were non-tenure-eligible assistant professors), while 55% of male faculty were promoted and tenured. Almost a third of women reported being discriminated against, compared with only 5% of men (p <.00001).

Conclusion: Substantial gender differences in the rewards and opportunities of academic medicine remain, that can not be attributed to differences in productivity or commitment between women and men.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Analysis of Variance
  • Arizona
  • Career Mobility*
  • Faculty, Medical*
  • Female
  • Humans
  • Least-Squares Analysis
  • Male
  • Physicians, Women / statistics & numerical data*
  • Salaries and Fringe Benefits
  • Schools, Medical*
  • Sex Factors
  • Surveys and Questionnaires