Debating the Evidence

Another AWIS Washington Wire in my inbox today. Here are a few tidbits I thought looked especially interesting:

Why Aren't More Women in Science? Top Researchers Debate the Evidence
This 248-page book is a collection of 15 essays by experts on gender differences in ability. They consider the question of why more women are not pursuing careers in science, engineering and math, considering innate differences, societal discouragements, differences in aspirations and other key factors. This book should challenge readers' emotional and political biases through empirical science.

This looks very interesting - and incredibly pricey. It's a lot cheaper on Amazon. Even so, I'm still debating whether I will order a copy or not. I have approximately 4,287 books on my bookshelf that I have not read yet (besides the 352 I have currently just barely started or half-read), and the thought of yet one more tome on sex differences makes me ill. I am so, so freaking sick of the sex differences debate. Women can do science and engineering. Men can be nurturing and emotional. Can we move on? Sigh. I suppose the answer is "no" and I'll have to keep dealing with this one unto my very death.

NIH Experience Mirrors that of NAS Report "Beyond Bias and Barriers" The NIH has been supporting post-doctoral training of large numbers of women for more than a decade, and reports mirror that of the NAS that the pipeline is not the problem in women continuing scientific careers. While men and women have been trained in roughly equal numbers for some time, women are hired and promoted at a much lesser rate.

There is a lot of tasty data in in this very short and very readable NIH piece. Here's one piece:

NIH sees these realities [that women are hired and promoted at a much lesser rate than men] reflected in our extramural funding patterns. Over the period from 1990 to 2004, the percentage of R01 awards going to women has increased only from 17 percent to 24 percent. Given that the success rates are so similar, there are clearly fewer women in a position to apply for these grants.

More from the wire:

Women Continue Gains in Science & Engineering Fields - Minorities Show Limited Progress Women have made substantial progress in preparing for careers in science and engineering (S&E), earning half (50%) of the bachelor's degrees, 44% of the master's and 37% of the doctorates awarded in S&E fields in 2003-04, according to the latest compendium of education, employment and demographic data, Professional Women and Minorities, published by CPST (the Commission on Professionals in Science and Technology). The gains in science and engineering by underrepresented minorities (URMs; African Americans, Hispanics, and Native Americans) have been slower, but overall, progress is being made. URMs earned 16% of the bachelor's degrees, 11% of the master's, and nearly 6% of the doctorates awarded in S&E in 2003-04.

Here's my complaint about this data: "women" are making gains but "minorities" show limited progress. Does this mean:

  • White women are making gains, minority women and men aren't, or
  • White women and minority women are making gains, minority men aren't, or
  • White women are making gains, minority men aren't, minority women aren't even in the picture?

It would be wonderful to have completely disaggregated data. Not disaggregating the data leaves minority women lost in the shuffle, I think.

More like this

UPDATE: Apparently it was not clear to some people that the second "quote" below is a parody written by me, of the first quote written by someone else. I hope this clears it up. You may want to advocate for gender equity in science and engineering. But you are just wasting your energy. Pat O'…
So, Chad posted a link to this post last week. As a woman in science myself, I have to say I don't 100% buy this argument: Most people go to work primarily in order to earn a paycheck. Workers prefer a higher salary to a lower salary. Jobs in science pay far less than jobs in the professions…
Tim left this comment over at Uncertain Principles on Chad's post The Pipeline Problem: I thought the data was pretty clear about this: past high school, the [physics] pipeline is no more leaky for women than it is for men...here's the Report: Read it for yourselves. Examination of the academic "…
The National Institutes of Health (NIH) has long been a key source of funding for medical research, but it wasn’t until 1986 that the agency formally established a policy of including women in clinical research. For decades, women received drugs and therapies that had been tested only on men, even…

Hi Zuska, I'm a little struck by your phrasing of the last question. The wire story seems to make it clear that it is only underrepresented minorities, namely African Americans, Hispanics, and Native Americans, who are not making gains. Yet your questions set up white women in opposition to minorities. Is it purely by accident that you left East Asian and South Asian people out of the picture? By force of habit, labeling the majority as white? Is this worth analyzing or am I making a big deal out of nothing?

By ThePolynomial (not verified) on 02 Feb 2007 #permalink

Years ago there was a book (still in press) called "But Some Of Us Are Brave: All the Women Are White, All the Blacks Are Men" We haven't made much progress since then. Indeed the current Council on Graduate Schools study on progression to the PhD reports data by race/ethnicity and by sex but does not break down racial/ethnic groups by sex. The current research study on PhD progression by the National Research Council is even worse. It is collecting NO data by sex. Feel free to call and complain.

Why they blame women and minorities for not making it through the ranks? Don't they realize that the people with the real control in this situation are the white males who dominate hiring committees?

Makes me wish I had a gender-ambiguous first name.
I also wonder how the racial/ethnic categories are defined. We (Americans) are so squeamish about explicitly defining our terms when it comes to race and so given to use euphemisms that the data gathering is already murky.
We ought to be at least as careful with these data as we are with our own.
Aside: Has anyone seen that show "30 Rock" where the black guy who went to Harvard's nickname is Twofer?