“She made a mean beef stroganoff”: Gendered portrayals of women in STEM in newspaper articles and their effects

ABSTRACT

Media articles about women in STEM often emphasize gender in ways that may reinforce stereotypes. In an archival study examining 172 articles from four major US and UK newspapers on women, Nobel laureates from 1903 to 2020, we find that over time, reporters are more likely to describe the scientist as a woman and less likely to mention her husband’s job. A follow-up experiment (N = 452) revealed no significant effects of an article that emphasizes the gender of a woman scientist on gender biases. These findings suggest that articles about women in STEM may emphasize gender rather than scientific accomplishments, but the ways in which they do so have changed over time and this emphasis may not affect readers’ gender bias.

KEYWORDS:

• Gender
• STEM
• journalism
• Nobel Prize

Acknowledgements

We are grateful to Mason Drusano for his help with the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data are available on the Open Science Framework: https://osf.io/j4bfv/.

Notes

1 As an additional exploratory analysis, we conducted 2 (narrative: gender emphasized or not emphasized) × 2 (school: public university versus liberal arts college) ANOVAs on the dependent variables. There were no significant interactions between narrative condition and school (all interaction Fs < 0.5, all ps > .50). (These analyses excluded the two participants who reported attending other schools.) We also conducted exploratory analyses examining participant race. Because of the relatively low numbers of participants in categories other than European-American/White, we compared White to non-White participants in our analysis to maintain statistical power. These analyses revealed no significant interaction between narrative condition and participant race on any of the dependent variables, all interaction Fs < 1.50, all ps > .20. However, we recognize that this approach is not ideal and may mask differences between racial or ethnic groups, so we have also provided a table of means and standard deviations by condition and race as supplementary material on the Open Science Framework: https://osf.io/bdgae. To further examine the relationship between year and the items from the Finkbeiner test, we calculated the ratio of articles containing each item over the total number of articles for each year and then conducted a correlation of year and that ratio. In this analysis, mentions of the laureate being a woman (r(39) = .21, p = .192) and mentions of her being the first woman (r(39) = .18, p = .251) are non-significant; however mentions of her husband’s job remain significant (r(39) = −.48, p = .002).