Tools and Resources | Duke Neurobiology

In many fields, men and women are not cited at the level that one would expect given their prevalence in the field (Dworkin et al., 2020; Zurn et al., 2020). While this situation arises due to systemic issues and may not be avoidable for specific papers, we can at least get a grasp of the situation and start to think about course corrections. We hope that these tools will help labs start to grapple with their role reflecting the representation in their respective fields and see if there are any blind spots that could be addressed. This list is a start and we plan on expanding it with more, and more relevant, tools for our department.

Dworkin, J. D., Linn, K. A., Teich, E. G., Zurn, P., Shinohara, R. T., & Bassett, D. S. (2020). The extent and drivers of gender imbalance in neuroscience reference lists. Nature Neuroscience, 23(8), 918–926. https://doi.org/10.1038/s41593-020-0658-y

Zurn, P., Bassett, D. S., & Rust, N. C. (2020). The citation diversity statement: A practice of transparency, A way of life. Trends in Cognitive Sciences, 24(9), 669–672. https://doi.org/10.1016/j.tics.2020.06.009

Gender Citation Balance Indexer

https://postlab.psych.wisc.edu/gcbialyzer/

This tool from our friends at UW Madison estimates the likelihood that a person with any given first name self-identifies as 'woman' or 'man' within the references of a manuscript. Those likelihoods are then compared to the relative distribution within the Journal of Cognitive Neuroscience. By looking at the first and last author it calculates the over or under representation of each gender combo cited in the manuscript based on the entire pool over the past decade.

To use, format the manuscript’s citations into APA 7th or other formats that include Crossref DOIs. Copy and paste into the top box and click ‘Submit’. After a short pause the output will be displayed below with additional explanations and interpretations.

Citation Transparency Chrome Extension

https://chrome.google.com/webstore/detail/citation-transparency/cepnbdbhabaljgecaddglhhcgajphbcf?hl=en

This tool can help mitigate this bias by making the perceived genders of first and last authors of papers more transparent in the search for references on Google Scholar and PubMed.

To use, click to add the extension in your Chrome session and once added right click the icon in the upper right toolbar to enable. After a slight delay papers listed in Google Scholar and PubMed will update with probabilistic gender information under the title. Some papers might not have enough information and will stay blank.

If you have any questions or comments please reach out to edi_neurobio@duke.edu