But what was really fascinating is the way they jumped on the methodologies of various studies in which the "gaydar" of test subjects was scored in evaluating groups in which half were gay and half were striaght.
From The Conversation:
But as we’ve been able to show in two recent papers, all of these previous studies fall prey to a mathematical error that, when corrected, actually leads to the opposite conclusion: Most of the time, gaydar will be highly inaccurate.
How can this be, if people in these studies are accurate at rates significantly higher than 50 percent?
There’s a problem in the basic premise of these studies: Namely, having a pool of people in which 50 percent of the targets are gay. In the real world, only around 3 to 8 percent of adults identify as gay, lesbian or bisexual.
What does this mean for interpreting the 60 percent accuracy rate? Think about what the 60 percent accuracy means for the straight targets in these studies. If people have 60 percent accuracy in identifying who is straight, it means that 40 percent of the time, straight people are incorrectly categorized. In a world where 95 percent of people are straight, 60 percent accuracy means that for every 100 people, there will be 38 straight people incorrectly assumed to be gay, but only three gay people correctly categorized.
Therefore, the 60 percent accuracy in the lab studies translates to 93 percent inaccuracy for identifying who is gay in the real world (38 / [38 + 3] = 92.7 percent). Even when people seem gay – and set off all the alarms on your gaydar – it’s far more likely that they’re straight. More straight people will seem to be gay than there are actual gay people in total.
H/T: Gay Times (UK)
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