| Literature DB >> 26938242 |
Daniel Storage1, Zachary Horne1, Andrei Cimpian1, Sarah-Jane Leslie2.
Abstract
Women and African Americans-groups targeted by negative stereotypes about their intellectual abilities-may be underrepresented in careers that prize brilliance and genius. A recent nationwide survey of academics provided initial support for this possibility. Fields whose practitioners believed that natural talent is crucial for success had fewer female and African American PhDs. The present study seeks to replicate this initial finding with a different, and arguably more naturalistic, measure of the extent to which brilliance and genius are prized within a field. Specifically, we measured field-by-field variability in the emphasis on these intellectual qualities by tallying-with the use of a recently released online tool-the frequency of the words "brilliant" and "genius" in over 14 million reviews on RateMyProfessors.com, a popular website where students can write anonymous evaluations of their instructors. This simple word count predicted both women's and African Americans' representation across the academic spectrum. That is, we found that fields in which the words "brilliant" and "genius" were used more frequently on RateMyProfessors.com also had fewer female and African American PhDs. Looking at an earlier stage in students' educational careers, we found that brilliance-focused fields also had fewer women and African Americans obtaining bachelor's degrees. These relationships held even when accounting for field-specific averages on standardized mathematics assessments, as well as several competing hypotheses concerning group differences in representation. The fact that this naturalistic measure of a field's focus on brilliance predicted the magnitude of its gender and race gaps speaks to the tight link between ability beliefs and diversity.Entities:
Mesh:
Year: 2016 PMID: 26938242 PMCID: PMC4777431 DOI: 10.1371/journal.pone.0150194
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Frequency of “genius” and “brilliant” per millions of words of text on RateMyProfessors.com, split by gender and discipline.
Fig 2Use of the words “brilliant” and “genius” on RateMyProfessors.com predicts the percentage of 2011 U.S. PhDs who are female.
Multiple regression analysis predicting female representation at the PhD level.
| Predictor | |||
|---|---|---|---|
| STEM indicator variable | −.39 | −1.27 | .230 |
| Brilliance language score | −.48 | −2.60 | .025 |
| Hours worked (on-campus) | .26 | 0.98 | .348 |
| Systematizing vs. empathizing | .01 | 0.04 | .971 |
| Selectivity | .10 | 0.54 | .597 |
| Quantitative GRE | −.53 | −1.62 | .134 |
| 77.9% |
* p < .05. N = 18 disciplines. “STEM” stands for “(Natural) Science, Technology, Engineering, and Mathematics.”
a Although Leslie, Cimpian, et al. [1] collected data on the number of hours worked off campus as well, they found that the number of hours worked on campus was a better predictor of female representation than the total number of hours worked. Thus, to be conservative, we included this stronger competitor in our regression analyses. However, the brilliance language score remains a significant predictor even when the total number of hours worked (on- plus off-campus) is used in the regression.
Fig 3Use of the words “brilliant” and “genius” on RateMyProfessors.com predicts the proportion of 2011 U.S. PhDs who are African American.
Multiple regression analysis predicting African American representation at the PhD level.
| Predictor | |||
|---|---|---|---|
| STEM indicator variable | −.32 | –0.79 | .447 |
| Brilliance language score | −.65 | –2.80 | .016 |
| Hours worked (on-campus) | −.20 | –0.53 | .607 |
| Selectivity | −.37 | −1.40 | .186 |
| Quantitative GRE | −.09 | –0.25 | .806 |
| 49.0% |
* p < .05. N = 18 disciplines. The brilliance language score was a significant predictor even in a model that included systemizing vs. empathizing (which was omitted from the main analysis above because it seemed uniquely relevant to the male vs. female contrast).
Multiple regression analysis predicting Asian American representation at the PhD level.
| Predictor | |||
|---|---|---|---|
| STEM indicator variable | .31 | 0.91 | .379 |
| Brilliance language score | −.22 | −1.14 | .275 |
| Hours worked (on-campus) | −.06 | −0.20 | .844 |
| Selectivity | .15 | 0.66 | .521 |
| Quantitative GRE | .60 | 2.06 | .062 |
| 65.1% |
~ p < .10. N = 18 disciplines.