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Gender stereotypes: The case of MisProfesores.com in Mexico

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  • Arceo-Gomez, Eva O.
  • Campos-Vazquez, Raymundo M.

Abstract

In this study we analyze the extent of gender stereotypes in student evaluations of college professors on the internet site MisProfesores.com in Mexico. We downloaded more than 600,000 evaluations for the period 2008–18. The evaluations include three scores on a scale of 0 to 10: how easy it is to obtain a good grade, how much the professor helps his or her students obtain good grades, and how clearly the professor presents the concepts of the course. The site also allows students to comment on the professor and the class, and we performed a quantitative text analysis of these comments. We found that women receive lower scores than their male counterparts, although the difference is relatively small: 1–2% of a standard deviation. Students refer more to the appearance and personality of female professors, and describe them more often as “bad” or “strict.” They also refer to women in less respectful terms, calling them “maestra” (“teacher”), but calling men “profesor” or “licenciado” (the title corresponding to their academic degree), and they use less positive language for women (“good” vs. “great” or “excellent” for men). Finally, words associated with qualities of service (traditionally stereotyped as feminine) favor women more than men; whereas, words with traditionally masculine associations have a negative impact on women's evaluations.

Suggested Citation

  • Arceo-Gomez, Eva O. & Campos-Vazquez, Raymundo M., 2019. "Gender stereotypes: The case of MisProfesores.com in Mexico," Economics of Education Review, Elsevier, vol. 72(C), pages 55-65.
  • Handle: RePEc:eee:ecoedu:v:72:y:2019:i:c:p:55-65
    DOI: 10.1016/j.econedurev.2019.05.007
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    References listed on IDEAS

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    1. Eva O. Arceo-Gomez & Raymundo M. Campos-Vazquez, 2014. "Race and Marriage in the Labor Market: A Discrimination Correspondence Study in a Developing Country," American Economic Review, American Economic Association, vol. 104(5), pages 376-380, May.
    2. Goldin, Claudia D. & Rouse, Cecilia, 2000. "Orchestrating Impartiality: The Impact of “Blind†Auditions on Female Musicians," Scholarly Articles 30703974, Harvard University Department of Economics.
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    10. Amanda Bayer & Cecilia Elena Rouse, 2016. "Diversity in the Economics Profession: A New Attack on an Old Problem," Journal of Economic Perspectives, American Economic Association, vol. 30(4), pages 221-242, Fall.
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    13. Cassandra M. Guarino & Victor M. H. Borden, 2017. "Faculty Service Loads and Gender: Are Women Taking Care of the Academic Family?," Research in Higher Education, Springer;Association for Institutional Research, vol. 58(6), pages 672-694, September.
    14. Linda Babcock & Maria P. Recalde & Lise Vesterlund & Laurie Weingart, 2017. "Gender Differences in Accepting and Receiving Requests for Tasks with Low Promotability," American Economic Review, American Economic Association, vol. 107(3), pages 714-747, March.
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    Cited by:

    1. Martin Flegl & Robert Hlavatý, 2022. "Understanding transitions in professors’ evaluation: the application of Markov chain," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 304-323, March.
    2. Kuhn, Andreas, 2022. "The Times Have Changed: Tracking the Evolution of Gender Norms over Time," IZA Discussion Papers 15621, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    Gender; Stereotypes; Big data; Teaching evaluations; Mexico;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • I20 - Health, Education, and Welfare - - Education - - - General
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • O54 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Latin America; Caribbean

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