"In an era when women are increasingly prominent in medicine, law and business, why are there so few women scientists and engineers? A new research report by AAUW presents compelling evidence that can help to explain this puzzle. Why So Few? Women in Science, Technology, Engineering, and Mathematics presents in-depth yet accessible profiles of eight key research findings that point to environmental and social barriers – including stereotypes, gender bias and the climate of science and engineering departments in colleges and universities – that continue to block women’s participation and progress in science, technology, engineering, and math."
Diane Auer Jones responds in today's Chronicle of Higher Education:
"What are the reasons for this persistent gap? According to the report, social and environmental factors are to blame. Shocking. Sadly, this report serves only to regurgitate age-old accusations and assumptions, and to make worn-out recommendations that we've heard so many times before—none of which have proven terribly effective in closing the gap in certain fields.
Research careers are highly competitive. No matter how long you've been at it, to be a successful researcher means competing against a growing group of applicants for a shrinking supply of grant and contract resources. As federal spending on interest and entitlement programs grow, the competition is only going to increase. Peer reviewers and contracting officials are compelled to give priority to those with the strongest track record and the highest likelihood of success, which generally means that the rewards are greatest for those who devote the most time and energy to their work.
This isn't gender bias. It is reality. There are rare exceptions among a few scientists who can focus intensely—or farm the work out to enough graduate students—that they get the job done with breathtaking efficiency. But for the most part, no dean or tenure policy in the world can change the fact that research careers are demanding and not very family friendly, because in general, being smart isn't nearly as important as being persistent, and persistence requires time. Designing better experiments is good, but being there to repeat them over and over again, in every possible iteration, is even better."
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