Gender-bias in peer reviewing might persist even when gender-equity is reached because both male and female editors operate with a same-gender preference whose characteristics differ by editor-gender.

Lockdowns in the United States caused by the COVID-19 pandemic appear related to a decrease in the number of women publishing research papers, especially as first authors.

How a letter addressing the lack of women invited to speak at a conference in brain stimulation encouraged researchers to take action.

There is a systemic bias in research evaluation, i.e., disciplines with a higher proportion of women have lower evaluations and funding success for all researchers, regardless of gender.

Blinding the initial review of applications for Beckman Young Investigator awards reduces prestige bias, but has no impact on the success rates for different genders.

Generative artificial intelligence, such as OpenAI’s ChatGPT, can be used to analyze scientific texts with specialized constructions, including peer review reports.

The gender gap in publication productivity has increased during the COVID-19 pandemic, with potential implications for the careers of women working in research.

An analysis of papers in which two or more authors shared first-author position found that male authors were more likely than female authors to appear first in the author list.

A text-mining study suggests that about half of the papers reporting the results of experiments on mice do not report the sex and age of the mice.