Summary of Sex and Gender Analysis Improves Science and Engineering

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For a long time, gender and sex have played a marginal role in scientific experiments and research, but this is changing. Evidence shows that taking gender and/or sex into account when designing research not only leads to new discoveries and better methodologies, but is often key to coming to the correct conclusions. In this whistle-stop tour through case studies from different disciplines, a group of scientists from various research institutions outline the importance and many benefits of including sex and gender analysis in scientific research.

About the Authors

Cara Tannenbaum is scientific director of the Institute of Gender and Health, Canadian Institutes of Health Research at the University of Montréal in Canada. Robert P. Ellis is lecturer and NERC Industrial Innovation Fellow in sustainable aquaculture at the College of Life and Environmental Sciences at the University of Exeter in the UK. Friederike Eyssel is professor at the Center of Excellence Cognitive Interaction Technology at Universität Bielefeld in Germany. James Zou is assistant professor of biomedical data science and, by courtesy, of computer science and of electrical engineering at Stanford University, CA in the United States. Londa Schiebinger is the John L. Hinds professor of history of science in the history department and director of the EU/US Gendered Innovations in Science, Health & Medicine, Engineering and Environment Project at Stanford University, CA in the United States.

 

Summary

The majority of scientific studies still don’t consider sex and gender-related variables.

The ability to reproduce an experiment is an important feature of any scientific study. In order to reproduce an experiment accurately, scientists need to know whether responses differed based on gender and/or sex. However, in the majority of scientific disciplines, male and female responses are pooled together, and there is no consistency in methodological reporting.

In some disciplines, like marine science and ecotoxicology, the percentage of studies that consider sex-based differences ranges from 23% down to 3.9%. In social robotics, scientists have only just started to investigate the implications of gender differences and stereotyping.

It’s easy to misinterpret data when disregarding sex and gender variables in scientific experiments.

Not distinguishing between male and female responses can skew results and lead to the incorrect interpretation of data. For example, melanoma and lung cancer patients respond differently to checkpoint inhibitors depending on their sex.

Similarly, women react to and report pain differently from men. Accounting for sex and ...


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