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Interesting thread on how accurately you can predict someone's gender with their answers to just 20 questions from a personality test. More than you might think, as it turns out.https://twitter.com/AndrewCutler13/status/1075535228792422400 …
Pretty bad, but ocean items were not made to tell sexes. I bet one can easily get near 100% with 10 well chosen items. (eg crying frequency)
Sure, I have no doubt that you can get close to 100% if you chose the questions specifically with predicting gender in mind, but in my opinion 65% ain't that bad when you just used 20 questions from a personality test that wasn't designed for that.
(I mean, at this pace, soon you'll be able to beat 65% just by asking *one* question, i. e. do you vote Republican or Democrat ^_^)
Okcupid questions were not designed to tell sex but I'm sure one can do better than 65pct using first 20 items, or random set of 20 items.
Yeah, fair enough, I wouldn't say I'm sure but it seems pretty likely when I think about it.
I knew I found this stuff before. Meta-analysis for sex diff in adult crying, d = .84, but non-normal data needs special treatment. https://books.google.dk/books?id=RHFYYwo9kREC&pg=PA60&lpg=PA60&dq=crying+frequency+by+gender&source=bl&ots=aoL7BjsADL&sig=SIT8pck8kc8hRoiW4HFOVaB6Blk&hl=da&sa=X&ved=0ahUKEwiEseHeoIDNAhXmFZoKHUgrDrYQ6AEIQTAG#v=onepage&q=crying%20frequency%20by%20gender&f=false … For kids, d = .19,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3432210/ …
Because the big 5 were originally designed to be able to differentiate a description of someone (or maximize variance) I assumed male/female would fall out a bit more. Then again, these 20 questions are way downstream from the original design.
IPIP uses 4 questions on each of the big5 to increase fidelity to that model. Doesn't try to maximize info about a person.
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