Managing “expectations of brilliance”

I just skimmed through this report that was recently published in Science:

Expectations of brilliance underlie gender distributions across academic disciplines. Leslie, Cimpian, Meyer, & Freeland. 16 January 2015: pp. 262-265.

Their summarized definition of the field-specific ability beliefs hypothesis is this: women are underrepresented in certain fields as a result of (i) a field-specific belief that one’s success in that field requires raw talent that cannot be taught and (ii) the cultural stereotype that men are more likely to possess this raw talent.  The authors support this hypothesis using a nation-wide survey of academics in both science, technology, engineering, and mathematics (STEM) as well as non-STEM disciplines.  In the survey, academics were asked to rate their own discipline, and these scores were combined to produce a discipline-specific measure of how much raw talent is required for their field.

The image below is the first figure from their paper. The x-axis corresponds to a synthesis of responses from academics about their specific discipline.  The y-axis corresponds to the percentage of Ph.D.’s in the field who are female.

In STEM fields, Math appears to be the field that requires the largest amount of raw talent, whereas Earth Science requires the least.  Physics, Engineering, and Computer Science, which all have notoriously low numbers in terms of women, are also rated higher on the “need to be brilliant” end.  One of the most interesting points about this work was that the hypothesis was also supported in non-STEM fields (Figure 1B).  The paper also shows that the hypothesis is supported among African American underrepresentation as well.

This paper brought up a number of questions for me.

  1. What’s up with Philosophy? Remember, these measurements of field-specific ability beliefs are determined from academics within the discipline.  I wonder if it’s the logic required behind philosophical arguments that leads to the high field-specific ability belief.
  2. The percentage of female Ph.D.s in a discipline is the measure of underrepresentation/overrepresentation.  In fact, this gender gap may begin in college, when students declare a major.
  3. The academics surveyed were faculty, postdocs, and graduate students – presumably all people who have obtained or are on their way to obtaining a Ph.D.  What if we surveyed 1,820 people from the general population instead of from this narrow slice?  Do the general population’s evaluation of field-specific ability beliefs align with the academic beliefs?  How does this correspond to the percentage of underrepresented groups in the major?
  4. As a soon-to-be faculty member that will span an historically underrepresented field (computer science) with an historically overrepresented field (biology) in terms of women involvement, will this new discipline become an average of the two in expectations of brilliance?  I think that it will make computer science more accessible, thereby reducing the belief that the discipline requires innate raw talent.  Only time will tell.

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