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Detecting Group Gender Stereotypes: Opinion-mining vs. Incentivized Coordination Games

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  • J. Jobu Babin

    (Western Illinois University)

Abstract

Individuals often make decisions based on perceived social norms and stereotypes. It is difficult to elicit such beliefs, since subjects often give inaccurate or "politically correct" responses to subjective, sensitive topics. This paper compares two methodological procedures meant to identify group beliefs. In an experimental setting, I pair a flat-rate, opinion-mining scheme with an incentivized coordination game and compare their effectiveness in identifying the well-documented Math-Gender stereotype. Following a simple math task prime, those in the baseline overwhelmingly stated they individually believed neither sex is inherently more proficient at mathematics, while 72% of those in the incentivized treatment said that they believed "males are more proficient" would be the modal response. Gender nor age drives this focal outcome, however, political orientation correlates to the perception of the stereotype. These results document the usefulness of an incentivized coordination game as a research tool and demonstrate how stereotypes persist independent of whether or not they are individually held or stated.

Suggested Citation

  • J. Jobu Babin, 2019. "Detecting Group Gender Stereotypes: Opinion-mining vs. Incentivized Coordination Games," Journal of Economic Insight, Missouri Valley Economic Association, vol. 45(1), pages 21-42.
    • Handle: RePEc:mve:journl:v:45:y:2019:i:1:p:21-42
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    Citations

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    Cited by:

    1. Nigel Burnell & Irina Cojuharenco & Zahra Murad, 2020. "He Taught, She Taught: The effect of teaching style, academic credentials, bias awareness and academic discipline on gender bias in teaching evaluations," Working Papers in Economics & Finance 2020-05, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    2. Dustan, Andrew & Koutout, Kristine & Leo, Greg, 2022. "Second-order beliefs and gender," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 752-781.
    3. Babin, J. Jobu & Chauhan, Haritima S. & Liu, Feng, 2022. "You Can’t Hide Your Lying Eyes: Honesty Oaths and Misrepresentation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 98(C).
    4. J Jobu Babin, 2020. "Linguistic signaling, emojis, and skin tone in trust games," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-14, June.
    5. Jobu Babin, J. & Hussey, Andrew & Nikolsko-Rzhevskyy, Alex & Taylor, David A., 2020. "Beauty Premiums Among Academics," Economics of Education Review, Elsevier, vol. 78(C).

    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory

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