Tuesday, November 4, 2014

Women in academic science: a changing landscape




  Are "young and midcareer women in math-intensive fields" . . .  "paid roughly the same (in 14 of 16 comparisons across the eight fields) as their male counterparts? As discussed below, the authors of the recent op-ed piece in the New York Times are disingenuous to suggest that the above graphs, based on NSF data and published in their journal article, indicate that rough parity has been reached for more junior women faculty, even if only in the left five categories (their "math-intensive" fields).

Based on the upcoming, extensive journal article,
Women in academic science: a changing landscape 
from which I extracted and plotted Figures 15-17 to make the figure above, the New York Times published an op-ed piece this past Sunday entitled:
"Academic Science isn't Sexist"
    
Now, we know that newspaper editors choose titles/headlines, so the title of the journal article itself better reflects the content of both that research article and of the op-ed piece.  However, right away, when the op-ed authors say they are relying on extensive data, rather than the anecdotes that commonly illustrate sexism, I am reminded of Michele Aldrich's article on the history of women in geology, where she points out that that history cannot help but be anecdotal, as the numbers are so small.  Granted, things are changing, as shown by the data presented in this article and elsewhere, especially NSF's extensive database.  However, that does not mean that "Academic science isn't sexist."  Less sexist, I would grant.

The authors lump the "math-intensive sciences" (geosciences, economics, engineering, math & computer science, physical sciences) contrasted with the non-math-intensive (life sciences, sociology, psychology) and compare how women are doing in academia in the two groups.  For starters, I know a lot of scientists who would bristle at life sciences (bio, above), if not psych and sociology, being less math intensive... anyway....   The authors note that women in their "math-intensive" fields, while underrepresented in numbers, are as successful as men once they make the first hurdle of a tenure-track job, and that women in the "non-intensive" fields are actually less successful by comparison.

One of the main points the authors want to make is that the most progress is now to be made at levels below the point of hiring at the tenure-track level.  [Their characterization of girls and boys is another whole realm of commentary.]  And indeed there is a LOT that can be done, of which one of the significant factors, they note, is MORE WOMEN TEACHING THOSE SCIENCES so that role models are available to women.  I don't disagree.  But the unfortunate title of the op-ed, and the fuzzy wording and conclusions by the authors, do academic women in science no favors.

Not surprisingly, there is a kerfuffle amongst academic scientists, particularly women (like me), and those who know and study them.  I read the op-ed and a couple of commentaries (and the comments on those commentaries), which sent me to the original article on which the op-ed is based.  I did not read all the text but I examined the figures, which are based primarily on data compiled by the National Science Foundation.  I have picked one subtopic to address the differences between op-ed text and actual data:  salaries of women scientists in academia.  Other commentaries bring up other issues.  Let me say that the authors do make some important points, I have no reason to vilify them.  But there are lies, damn lies, and statistics...

Are "young and midcareer women in math-intensive fields" . . .  "paid roughly the same (in 14 of 16 comparisons across the eight fields)" as their male counterparts?

The op-ed states, with the part I will address in bold:
"Our analysis reveals that the experiences of young and midcareer women in math-intensive fields are, for the most part, similar to those of their male counterparts: They are more likely to receive hiring offers, are paid roughly the same (in 14 of 16 comparisons across the eight fields), are generally tenured and promoted at the same rate (except in economics), remain in their fields at roughly the same rate, have their grants funded and articles accepted as often and are about as satisfied with their jobs"

Look at the figure (their figures).  [If you go to the original you will see that not all the data are significant (significant data they note with asterisks, etc.).]  I took the figures and put a line across the graphs at 100% (that is, parity) to look at how often women made more or less than 100% what men made.  Let's leave out the full professors, because they are not "young and midcareer."  At that level, the history of discrimination is apparent.

If women were paid "roughly the same" as men, shouldn't there be as many columns above the 100% line as below?  Yet out of 32 columns, only five are above the 100% line. More disturbing in terms of progress is that there appears to be more parity at the Associate Professor rank than the Assistant Professor rank -- that is, if you add up the white space below and color above the 100% line for all columns, there is more white below (and less color above) on the Assistant Professors' graph.

This difference might be because women spend longer in the Associate Professor rank, so their salaries rise, albeit at the expense of not getting the Full Professor boost till later in their careers, thus not as fast as men's.  Alternatively, it could be that women in all categories are earlier in their careers, on average, because of the only-quite-recent increase in hiring of women.  But more analysis would be needed to evaluate these differences.

No matter the reasons for the differences, I think the authors are disingenuous, at best, to use these data to say that junior and mid-career women are paid "roughly the same" as men in the same rank.

P.S.  It appears that the "14 of 16" comes from taking the 2010 data from not just what the authors define as "math intensive" fields.  If considering ONLY math-intensive fields (by their definition), the number would be out of 10 (if only 2010) or out of 20 (the latter if including 1995).  If considering only statistically significant differences (or not), the numbers for the "math-intensive" fields would be 9 of 10 for 2010 or 16 of 20 for 1995 plus 2010.  The eight fields would include all the sciences surveyed.  And of course all sciences use math, so the real difference is the fields where women are more under-represented.


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