Home

Menu

Loading wiki pages...

View
Wiki Version:
<h2>Project Overview</h2> <p>This repository documents data and code for:</p> <p>O'Dea<em>, R. E., Lagisz</em>. M., Jennions, M. D. & Nakagawa, S. Gender differences in individual variation in academic grades fail to fit expected patterns for STEM. <strong><em>Nature Communications</em></strong>, 9, 3777 (2018). DOI: <a href="http://dx.doi.org/10.1038/s41467-018-06292-0" rel="nofollow">10.1038/s41467-018-06292-0</a></p> <p>*contributed equally to this work</p> <h3>Component Pages</h3> <h4>Data</h4> <ul> <li>Raw and processed data on teacher-assigned grades for female and male students from grade 1 onwards </li> </ul> <h4>Code</h4> <ul> <li>R code used to process, impute, and analyse data, and produce figures and tables presented in the manuscript </li> </ul> <h4>PISA Analysis</h4> <ul> <li>A supplementary analysis of standardised test scores </li> </ul> <h3>Abstract</h3> <p>Fewer women than men pursue careers in Science, Technology, Engineering, and Mathematics (STEM), despite girls outperforming boys at school in the relevant subjects. According to the ‘variability hypothesis’, this over-representation of males is driven by gender differences in variance; greater male variability leads to greater numbers of men who exceed the performance threshold. Here, we use recent meta-analytic advances to compare gender differences in academic grades from over 1.6 million students. In line with previous studies we find strong evidence for lower variation among girls than boys, and of higher average grades for girls. However, the gender differences in both mean and variance of grades are smaller in STEM than non-STEM subjects, suggesting that greater variability is insufficient to explain male over-representation in STEM. Simulations of these differences suggest the top 10% of a class contains equal numbers of girls and boys in STEM, but more girls in non-STEM subjects.</p>
OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
Accept
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.
Accept
×

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.