+What are the reasons a male-to-female transition might seem like a good idea to someone? _Why_ would a male be interested in undergoing medical interventions to resemble a female and live socially as a woman? I see three prominent reasons, depicted as the parents of the "transition" node in a graph.
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+First and most obviously, femininity: if you happen to be a male with unusually female-typical psychological traits, you might fit into the social world better as a woman rather than as an anomalously effeminate man.
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+Second—second is hard to quickly explain if you're not already familiar with the phenomenon, but basically, autogynephilia is very obviously a real thing; [I wrote about my experiences with it in a previous post](/2021/May/sexual-dimorphism-in-the-sequences-in-relation-to-my-gender-problems/). Crucially, autogynephilic identification with the _idea_ of being female, is distinct from naturally feminine behavior, of which other people [know it when they see it](/2022/May/gaydar-jamming/).
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+Third—various cultural factors. You can't be trans if your culture doesn't have a concept of "being trans", and the concepts [and incentives](/2017/Dec/lesser-known-demand-curves/) that your culture offers, make a difference as to how you turn out. People who think of themselves as trans women in today's culture, could very well be "the same" as people who thought of themselves as drag queens or occasional cross-dressers 10 or 20 or 30 years ago. (Either "the same" in terms of underlying dispositions, or, in many cases, just literally the same people.)
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+If there are multiple non-mutually-exclusive reasons why transitioning might seem like a good idea to someone, then the decision of whether to transition could take the form of a liability–threshold model: males transition if the _sum_ of their femininity, autogynephilia, and culture-related-trans-disposition exceed some threshold.
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+So where do the two types come from? This graph is just illustrating (conjectured) cause-and-effect relationships, but if we were actually to flesh it out as a complete Bayesian network, there would be additional data that quantitatively specifies what (probability distribution over) values each node takes conditional on the values of its parents. When I claim that Blanchard–Bailey–Lawrence's two-type taxonomy is a useful approximation for this causal model, I'm conjecturing that the distribution represented by this Bayesian network (if we had the complete network) can also be approximated a two-cluster model: _most_ people high in the "femininity" factor will be low in the "autogynephilia" factor and _vice versa_, such that you can buy decent predictive accuracy by casually speaking as if there were two discrete "types".
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+[The sexual orientation node increases femininity and decreases AGP, so those pathways are anti-correlated; however, the fact that straight AGP men also vary somewhat in their degree of femininity; some informal accounts (link Sailer) have emphasized how masculine (even hypermasculine) AGPs are, but this seems wrong]
+[briefly mention ETLE]
+[Berkson's paradox is also a thing]
+[People who don't quite seem to fit the coarse taxonomy might still be explained by the graph and a threshold model]
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+Why do I believe this? Anyone can name some variables and sketch a directed graph between them. Why should you believe this particular graph is _true_? Ultimately, the reader cannot abdicate responsibility to think it through and decide for herself, but it seems to _me_ that all six arrows in the graph are things that we separately have a pretty large weight of evidence for, either in published scientific studies, or just informally looking at the world.
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+[femininity->transition would be obvious even if it weren't in th]