And these are the averages. Which means for every answer that accurately said 1%, someone said 39% (or two people said 30%)
Which means they think if they know two other people, one of them must be trans. Or more likely, that entire cities of “others” (that they’ve never been to) must be trans.
I feel like this is largely because if you can identify one trans woman, and are right, you think everyone who looks that way is also one. (Because sorry transmasc, you don’t exist to society as anything more than feminine gay man)
Which is why cis women, especially butch women, are frequently accused of being trans… we don’t meet the stereotype of femininity, and thus must be men, rather than just… women who aren’t hyperfeminine…
I’d like to know how large their sample size was. I mean, this was yougov, so I expect at least some level of credibility to this, but depending on how large the same size is and how biased your selection is, you can get some really weird numbers.
E.g. do the same study with some old KKK members or with a school class in a black, impoverished neighbourhood or with a group of CEOs and you will get very different results.
And these are the averages. Which means for every answer that accurately said 1%, someone said 39% (or two people said 30%)
Which means they think if they know two other people, one of them must be trans. Or more likely, that entire cities of “others” (that they’ve never been to) must be trans.
I feel like this is largely because if you can identify one trans woman, and are right, you think everyone who looks that way is also one. (Because sorry transmasc, you don’t exist to society as anything more than feminine gay man)
Which is why cis women, especially butch women, are frequently accused of being trans… we don’t meet the stereotype of femininity, and thus must be men, rather than just… women who aren’t hyperfeminine…
I’d like to know how large their sample size was. I mean, this was yougov, so I expect at least some level of credibility to this, but depending on how large the same size is and how biased your selection is, you can get some really weird numbers.
E.g. do the same study with some old KKK members or with a school class in a black, impoverished neighbourhood or with a group of CEOs and you will get very different results.