In yesterday’s NYT, a piece on “The Science of ‘Gaydar’ ” by Joshua A. Tabak (a doctoral candidate in social and personality psychology at the University of Washington) and Vivian Zayas (an assistant professor of psychology at Cornell). The short summary:
“Gaydar” colloquially refers to the ability to accurately glean others’ sexual orientation from mere observation. But does gaydar really exist? If so, how does it work?
Our research, published recently in the peer-reviewed journal PLoS ONE, shows that gaydar is indeed real and that its accuracy is driven by sensitivity to individual facial features as well as the spatial relationships among facial features.
We conducted experiments in which participants viewed facial photographs of men and women and then categorized each face as gay or straight. The photographs were seen very briefly, for 50 milliseconds, which was long enough for participants to know they’d seen a face, but probably not long enough to feel they knew much more. In addition, the photos were mostly devoid of cultural cues: hairstyles were digitally removed, and no faces had makeup, piercings, eyeglasses or tattoos.
Even when viewing such bare faces so briefly, participants demonstrated an ability to identify sexual orientation: overall, gaydar judgments were about 60 percent accurate.
… Consider, for example, facial width-to-height ratio. This is a configural physical feature that differs between men and women (men have a larger ratio) and reflects testosterone release during adolescence in males. Given that stereotypes of gender atypicality — gay men as relatively feminine and gay women as relatively masculine — play a role in how people judge others’ sexual orientation, our finding suggests that cues like facial width-to-height ratio may contribute to gaydar judgments.
Another novel finding: in both experiments, participants were more accurate at judging women’s sexual orientation (64 percent) than at judging men’s (57 percent). Lower gaydar accuracy for men’s faces was explained by a difference in “false alarms”: participants were more likely to incorrectly categorize a straight man as gay than to incorrectly categorize a straight woman as gay.
Why might “false alarm” errors be more common when judging men’s sexual orientation? We speculate that people overzealously interpret whatever facial factors lead us to classify men as gay. That is, it may be that straight men’s faces that are perceived as even slightly effeminate are incorrectly classified as gay, whereas straight women’s faces that are perceived as slightly masculine may still be seen as straight. That would be consistent with how our society applies gender norms to men: very strictly.
On 60 percent accuracy — which indicates that gaydar is certainly imperfect:
Since chance guessing would yield 50 percent accuracy, 60 percent might not seem impressive. But the effect is statistically significant — several times above the margin of error. Furthermore, the effect has been highly replicable: we ourselves have consistently discovered such effects in more than a dozen experiments, and our gaydar research was inspired by the work of the social psychologist Nicholas Rule, who has published on the gaydar phenomenon numerous times in the past few years.
That is, the effect is real but subtle.
On the word gaydar and the -dars it spawned:
-dar: gaydar ‘ability to detect that people are gay’ (gay + radar, the second historically an acronym) motivated a pile of other -dar portmanteaus (Language Log discussions here, here, and here), so that eventually -dar came to be seen as a formative on its own [a libfix], usable with bases other than monosyllables (from jewdar and blackdar, eventually to humordar and sarcasmdar) and conveying not just ‘ability to detect people in some social group’ but more generally ‘ability to detect some quality’. (link)