blog 10
@Summers
First things first, the actual problem. You start out addressing the issue of representation of women in tenured positions in the sciences and engineering as just that, a problem. Recognizing this as a problem is important, and given that you described the topic of your talk as “diversifying�, it seemed natural that the agenda was going to be focused on what can be done to help solve this problem. However, this was not the focus of the discussion. Instead, the talk seemed focused on justifying the current way that things are. The example of the three “hypothesises� (and no, I don't think you were using the word 'hypotheis' correctly) comes to mind, where you presented three different potential causes of underrepresented women in the these fields. It wasn't until very late in your talk that you even addressed issues relating to what can be done to better the situation. Even then the talk digressed into relating to child care, a connection that makes no sense from a gender equality position.
Ignoring the notion that the talk didn't really address the problem, and instead focused heavily on “hypothesises� about why we are in the current situation, there are still countless issues that need to be considered about the logical progression of your arguemnts. Your first hypothesis relies on the assumption that women more proportionally don't want to commit to a workload (for example) of 80 hours weeks, and that men are more likely agree to such a task. Disproportional unmarried women and women without children seems to make sense, but it ignores the general sexists notions that women are primary child givers. It's an underlying problem, and relying on it as an assumption isn't going to help things. The second “hypothesis� relies on the assumption that overall IQ and mathematical/scientific ability can be quantified in the same way the height can. This is a very heavy concern of Fausto-Sterling. The long and the short, those statistics don't support enough of a difference to be scientific, and the ways in which they're tested are not something that we can call objective. There is too much in question to rely on them in this way.
We can't make accurate gains toward equality by making logical mistakes like basing our assumptions inequality in the first place, and we can't take statistics about very complicated matters (such as intelligence that many will attribute simply cannot be quantified) and start basing judgments about the “way things are� with offering serious scrutiny.