National differences in gender-science stereotypes predict national sex differences in science and math achievement (Nosek et al., 2009, PNAS)

citation

Nosek, B. A., Smyth, F. L., Sriram, N., Lindner, N. M., Devos, T., Ayala, A., Bar-Anan, Y., Bergh, R., Cai, H., Gonsalkorale, K., Kesebir, S., Maliszewski, N., Neto, F., Olli, E., Park, J., Schnabel, K., Shiomura, K., Tulbure, B., Wiers, R. W., Somogyi, M., Akrami, N., Ekehammar, B., Vianello, M., Banaji, M. R., & Greenwald, A. G. (2009). National differences in gender-science stereotypes predict national sex differences in science and math achievement. Proceedings of the National Academy of Sciences, 106, 10593-10597. [Request Paper]

Abstract

About 70% of more than half a million Implicit Association Tests (IATs) completed by citizens of 34 countries revealed expected stereotypes associating science with male more than with female. We discovered that nation-level implicit stereotype predicted nation-level sex differences in 8th-grade science and mathematics achievement. Self-reported stereotypes did not provide additional predictive validity of the achievement gap. We suggest that implicit stereotypes and sex differences in science participation and performance are mutually reinforcing, contributing to the persistent gender gap in science engagement.

Study Demos

Data for the Implicit Association Tests were collated across public data collections of the "gender-science IAT" hosted by Project Implicit from July 27, 2000 to July 25, 2008. The "gender-science IAT" continues to be one of the demonstration tasks hosted at https://implicit.harvard.edu/ at the main demonstration site and all of the international sites (see flags at the link). The task requires about 10 minutes to complete.

Study Materials

The TIMSS website has a variety of reports, resources, and background information on the TIMSS achievement tests that were the data for math and science achievement for this article. The SI Appendix has additional information about materials and measures.

Data

Three datafiles are available at Brian Nosek's dataverse that are sufficient for reproducing the analyses reported in this article.

Sample media Coverage

Mathe + Chemie = männlich, Süddeutsche Zeitung [German]

BBC News World Service Interview

Sydney Morning Herald [English]

Supplements

The primary supplement is called SI Appendix and is also available directly from the PNAS website. That appendix contains numerous links to analysis outputs. Links to those outputs are also listed here:

CORR.GDPandGGI.html,
ST1.countrystats.pdf,
ST2.keycorrelations.pdf,
ST3.GLM.8thscidif03.html,
ST4.GLM.8thmathdif03.html,
ST5.GLM.8thscidif99.html,
ST6.GLM.8thmathdif99.html,
ST7.GLM.allDVs.unweighted.html,
ST8.GLM.allDVs.mid90pctIAT.html,
ST9.REGdiag.BGscidiff03onIAT.WEIGHTED.html,
ST10.REGdiag.BGmathdiff03onIAT.WEIGHTED.html,
ST11.REGdiag.BGscidiff99onIAT.WEIGHTED.html,
ST12.REGdiag.BGmathdiff99onIAT.WEIGHTED.html,
ST13.REGdiag.BGscidiff03onIAT.UNweighted.html,
ST14.REGdiag.BGmathdiff03onIAT.UNweighted.html,
ST15.REGdiag.BGscidiff99onIAT.UNweighted.html,
ST16.REGdiag.BGmathdiff99onIAT.UNweighted.html,
ST17.RaceIATanalysis.covariates.html,
ST18.AgeIATanalysis.covariates.html,
GLM.8thmathdif03.covariatesimpact.html,
GLM.8thmathdif99.covariatesimpact.html,
GLM.8thscidif03.covariatesimpact.html,
GLM.8thscidif99.covariatesimpact.html,
GLM.REVERSE.8thmathdif03.html,
GLM.REVERSE.8thmathdif99.html,
GLM.REVERSE.8thscidif03.html,
GLM.REVERSE.8thscidif99.html,
CORR.IATandTIMSS039995.html

Home pages: Brian Nosek, Fred Smyth