Dataset for: Gender bias in (neuro)science: facts, consequences and solutions Jessica Schrouff Doris Pischedda Sarah Genon Gregory Fryns Ana Luisa Pinho Eliana Vassena Antonietta Gabriella Liuzzi Fabio Santos Ferreira 10.6084/m9.figshare.7768073.v1 https://wiley.figshare.com/articles/dataset/Dataset_for_Gender_bias_in_neuro_science_facts_consequences_and_solutions/7768073 Women neuroscientists (please note that we refer to all who identify as such) are still underrepresented in various aspects of academic life. The efforts of the community to mitigate this issue are growing but can elicit adverse reactions (Moghaddam & Gur, 2016). In this opinion paper, we discuss the different approaches that have been taken at institutional, organizational and individual levels to counter gender bias and aim at addressing unfavorable comments. We base our reasoning on empirical data and on the feedback received after the release of the Women in Neuroscience Repository (WiNRepo, see Supplementary Table S1.a), an initiative we created to increase the visibility of women in neuroscience. While this feedback originated mainly from oral conversations and was not rigorously quantified, we believe the frequency of the comments justify their discussion, as performed in (Moghaddam & Gur, 2016). The aim of this piece (supported by a list of signatories, see Supplementary Table S2) is therefore to ‘debunk the myths’ related to gender bias and to affirmative actions in academia, as well as to propose concrete measures that can been implemented to counter such bias. 2019-08-01 14:02:42 women in neuroscience affirmative actions gender balance women underrepresentation Neuroscience