The Myth of Meritocracy and the Matilda Effect in STEM: Paper Acceptance and Paper Citation

TL;DR

This paper discusses gender biases in STEM academia, proposing double-blind reviews and anonymized author identification to reduce bias in paper acceptance and citation, and encourages further gender-focused reforms.

Contribution

It introduces practical modifications like double-blind review and anonymized author info to mitigate gender bias in STEM publishing and citations.

Findings

Gender bias affects paper acceptance and citations in STEM.

Proposed modifications can help reduce gender bias.

Encourages gender-segregated data collection for further research.

Abstract

Biases against women in the workplace have been documented in various studies. There is also a growing body of literature on biases within academia. But particularly in STEM, due to the heavily male-dominated field, studies suggest that if one's gender is identifiable, women are more likely to get their papers rejected and not cited as often as men. We propose two simple modifications to tackle gender bias in STEM that can be applied to (but not only) IEEE conferences and journals. Regarding paper acceptance, we propose a double-blind review, and regarding paper citation, we propose one single letter to identify the authors' first names, followed by their family names. We also propose other modifications regarding gender bias in STEM and academia and encourage further reforms supported by current research on this topic with gender-segregated data.