Workload and reduced fecundity — try not to work too hard, ladies

Here’s a vaguely misogynistic study for you.  This article, “Women who work or lift a lot may struggle to get pregnant,” discusses the findings from a recent paper in Occupational and Environmental Medicine.  The authors surveyed women trying to conceive in the Nurses’ Health Study 3, a large cohort of predominantly Caucasian nurses.  Their covariates of interest were how many hours per week women worked and how often they lifted more than 25 lbs in a day; the primary outcome was time to conception.  The authors concluded,

Working more than 40 hours a week was linked with taking 20 percent longer to get pregnant compared to women who worked 21 to 40 hours.

Moving or lifting at least 25-pound loads several times a day was also tied to delayed pregnancy, extending the time to conception by about 50 percent.

The unstated interpretation is that women’s bodies can’t handle working a full day or lifting any weight, so women at reproductive age should think twice about what they do for a living.

Here’s the original paper.

One potential issue is that the study is cross-sectional and the authors didn’t actually follow the women from the time of first interview until they got pregnant.  Instead, they used one survey to ask how long the women had been trying to conceive, then used a survival analysis method to estimate the time to pregnancy based on the self-reported times.  This method of analysis is biased: women who had no trouble conceiving are underrepresented in the sample and women who have taken a long time to get pregnant are overrepresented.  Furthermore, we don’t know the true outcomes for these women, only the ones estimated by a parametric model.

My biggest issue with this study is that they attach any meaning to their findings at all, saying that working more has a “detrimental impact on female nurses’ ability to get pregnant”.  They use duration of pregnancy attempt “as a surrogate for fecundity”.  Fecundity implies some biological ability to reproduce.  However, using time to conception as a proxy for fecundity relies on the assumption that everyone is trying equally hard to get pregnant.  If that were the case, then any variation in time to conception would be due to fecundity.  This isn’t something they checked or measured, and differences in women’s ideas of what “trying to get pregnant” means are probably what’s actually driving the trend the authors reported.

The Reuters article quoted someone sensible:

“If this effect is real, it is likely due to the fact that these women are having less frequent intercourse due to their work demands,” Lynch, who wasn’t involved in the study, said by email.

Nobody needed to do a study to figure that out.  Anyway, we could come up with all sorts of other plausible explanations for why women who work more are having less frequent intercourse.  If they redid this study on a cohort of women working in tech, I’m sure they’d find a similar relationship between number of hours worked and time to conception.  The point is, working more hours or picking up 25 lb boxes probably has no effect on anyone’s biological capacity to reproduce.  The authors are making a mountain out of a molehill.

I routinely lift 100 lbs over my head, so I guess I’ll really be screwed when I want to have a baby.

Female instructors should not get bonus points to correct for gender bias

A slough of research has come out in the last few years (and there’s more forthcoming from my collaborators and me) showing that these end-of-semester ratings that students give teachers, usually on a scale from 1-5 or so, are significantly biased against female professors. The obvious question is: if not student evaluations of teaching (SET), how should we evaluate instructors? I recently saw this article on Twitter.  It argues that “female faculty should receive an automatic correction” on their SET scores, meaning that the administration would add a fixed number to every female instructor’s score in order to make it comparable to male instructors’ scores. This adjusted score would be used to decide whether the instructor should be rehired to teach, be given tenure, etc.

I don’t believe this can be done, for a number of reasons. There are other biases and confounding variables besides gender that make it impossible to find a single number to add to every female instructor’s score.

  • Biases are not consistent across fields. For example, at Sciences Po in Paris, there is a greater proportion of female instructors in sociology than in economics, and the observed gender bias is less in sociology than in economics.  Any correction to SET would have to vary by course matter.
  • Biases depend on student gender as well. Our research shows that in some schools, male students rate their male instructors significantly higher than their female instructors while female students tend to rate them the same.  This is a problem for adjusting scores because the gender balance in the class will affect the instructor’s score. For instance, imagine a hypothetical male instructor who teaches two identical classes. On average, his male students give him a rating of 4.5 and females give him a rating of 4.  In the first class, the gender balance is 50/50, so the average rating is 4.25.  In the second class, there are 80 males and 20 females, so the average rating will be 4.4.  There’s no one magic number to add or subtract from this average to cancel out the gender bias when comparing this score to the SET of other instructors.
  • There is some evidence that SET are biased by the instructor’s race and age as well.  We lack data on this, but similar work on bias in hiring decisions has showed that people (men and women alike) comparing identical resumes will tend to prefer job applicants with male, European-sounding names.  Anecdotally, instructors who have accents or are above average age (even as young as mid-thirties in some places!) fare worse on their SET.

The list could go on — I’m sure there are a ton of other confounding variables, like time of day of the class, difficulty of the course material, etc. which affect how students tend to rate their instructors.  In order to find a correcting factor for each female instructor, you’d have to look at all of these variables and average them out.  In fact, you ought to do that for male instructors too, since gender isn’t the only bias.  This just highlights the fact that SET aren’t measuring teaching effectiveness in the first place; they’re a better measure of how comfortable or satisfied a student is in the class.

Admittedly, the title of this post sounds combative. But it’s not — of course something needs to be done about the pervasive gender bias that’s causing female faculty to lose teaching positions and costing them job promotions.  I’m merely arguing that it is impossible to effectively “correct” for gender bias, and so alternative, more objective means for evaluating teaching effectiveness should be used instead of SET.