When it comes to gender, science suffers from what has been called a "leaky pipeline." In some fields, like biology, women make up the majority of the individuals entering graduate school in the field. But at each successive career stage—post-doctoral fellowships, junior faculty, tenured faculty—the percentage of women drops . The situation is even worse in fields where women are in the minority at the graduate level.
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It's difficult to figure out why so many women drop out of the career pipeline. Progressing through a research career is a struggle for everyone, and it can be tough to suss out subtle sources of bias that can make it harder for women to push through. It's possible to do statistical analyses of outcomes—say, how many women received a particular type of grant—but then it becomes hard to determine whether they were all equally qualified. It's possible to set up artificial test situations that are better controlled, but people's behavior changes when they know they're being tested.
That is precisely the message that's driven home by a new paper that looks at gender bias in the awarding of research positions in France. While the study has some significant limitations, it examined the outcomes in two situations: the year the test was announced and all the people on the award committees were aware of it, and the year after, when the same people returned but had probably not realized the test was being repeated.
Bias, overt and otherwiseIn France, allocation of research positions at elite institutions is done through a two-step process. Candidates are first selected based on a set of predetermined criteria (such as number of publications and their impact). Those that clear this cut off are all highly qualified; at that point, a committee of scientists in their field looks at intangibles and other hard-to-quantify aspects of the applicants' research careers. A Canadian-French team of scientists received access to this process and was able to track the outcomes of the committee's decisions for two years.
“So the detailed observations of the middle corona that we make at eclipses will remain unique for the foreseeable future.” He adds that the new telescope also can’t generate wide-field views the way smaller telescopes can during eclipses—allowing for study of the farthest reaches of the coronal footprint—nor can it match the resolution of the instrumentation on the Solar and Heliospheric Observatory now in orbit around Earth.
To an extent. While there were over 400 committee members, information on how they voted for different candidates was kept confidential. All that could be determined was whether the committee as a whole had chosen them for a research position.
The first year the test was run, the researchers got all the committee members to take a standard test for what's called implicit bias . This is the sort of thing that people do without thinking, like unconsciously associating being a scientist with being male. While this is typically not a bias people are even aware of—it's common in women and among those who push for greater gender equality—it is associated with differences in women's participation in the sciences.
Afield with the Gar Professor
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Sign up for the Daily newsletter and never miss the best of WIRED.These tests showed that, when it comes to implicit bias, the French scientists were equivalent to France as a whole, in that there was a significant tendency to associate science success to being male.
But, ideally, scientists are a relatively rational bunch, and these were involved in a deliberative group activity. So, the hope is that at least some of them would be able to overcome this implicit bias. The authors' hypothesis is that, if people are thinking about the potential for bias, they'll be more likely to overcome their implicit biases.