Cordelia Fine combats neuro-sexism

Over the past year, many QAECo members have been discussing issues of gender and science. We’re concerned about the representation of women in leadership roles, balancing career expectations and aspirations with personal lives and responsibilities, and the unconscious gender biases that plague us all. We’ve engaged in personal confessions, journal clubs, critique of university policy, and some relaxed ladies’-lunching.

A major recent influence on my own conscious gender attitudes has been Cordelia Fine’s Delusions of Gender. It’s cleverly titled, scattered with sarcasm and lays out an argument that appeals enormously to me (hello, confirmation bias). Fine contends that there’s very little, if any, evidence that male and female brains are inherently different. Our brains are highly plastic, constantly soaking up cues from our gender normative environment, and have likely done so since even before we were born. Fine critiques many studies that claim males and females are ‘hard-wired’ to behave differently, revealing problematic study designs and biased interpretations.

In discussing the framing of gender studies, Fine also traces changes in attitudes towards gender differences. She quotes century-old assumptions that now seem hilarious, arrogant and unscientific, and wonders what present-day beliefs might be similarly dismissed in the future. For me it’s ultimately a heartening, rather than a frustrating, story. We’ve not yet arrived, I can contribute to a shift towards gender equity and it’s our culture, not my ‘hard-wiring’, that’s the primary limitation. Let’s do this!

Cordelia Fine was kind enough to visit QAEco earlier this month and share some of her more recent work. She focused on erroneous attributions of gender difference to studies using fMRI techniques, a topic that comes through in Delusions. However she delved further into a critique of the typical statistical analyses of the field – a topic close to many a QAEcologists’ heart! – and made some great points about the perils of post hoc data interpretation. I was surprised to leave the lecture reflecting more on the way I approach science than the way I approach gender issues.


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