tyr_13
Penultimate Amazing
- Joined
- Aug 8, 2008
- Messages
- 18,095
Judge all you want! I'm not going to agree (especially since you refuse to give an argument for "correct pronouns") but I also don't think you are harming or helping anyone thereby.
You simply reject the argument that the existence of butch women (and Bishōnen men) and transgender people means it's wrong to just insist your initial perception be given the overwhelming weight. Pretending this has been discussed just because you reject it is, well it isn't intellectually honest.
I'm well aware you disagree. It just doesn't matter. Like, at all. You know what I'm saying when I say that, which you claim to be your overriding concern.
Bzzzzzt. Can I quickly note the irony of trying to tell someone else what is happening in their own head, while arguing for uncritical acceptance of people's ability to introspect on the matter of gender?
It's not happening only 'in your own head'; I'm reading what you wrote.
Again, what you wrote means you actually do care about others being judged, otherwise what you said isn't sarcastic. More than that, you object a lot to the judgement with your above 'prove to me it's even wrong to misgender' argument.
The turd plating just isn't that elegant.
Nope, I have more constraints than that and I even spelled them out: "All that matters to me is that I can tell which pronouns are pointing to which nouns in any given flow of conversation."
ETA: I'll ask again about poor ignorant Carl, the proverbial freshman at CU Boulder. What is the best argument that he needs to update his heuristic for pronoun assignment, aside from "We will judge you morally inferior if you don't comply."
Right, because your perception is paramount over not just the subject, but the other people in the conversation.
Which ties nicely into the obvious reason Carl, who you think shouldn't adapt from the gendered language of livestock, should care; to give a flip about other people. Why make the change? To be respectful, polite, and kind to the people who get misgendered a lot. That's it. Basic empathy isn't enough for a lot of you, I know that already, but that doesn't mean it's a bad reason for Carl or anyone who doesn't give their own avoidance of having to give some actual thought to who is being talked about primary importance.
Hence 'don't be a jerk'.
Do you remember the name or author of any of the subsequent papers, or have a link, so I don't have to paw through each one? The first one I looked at didn't say anything about 94%.
I think it was the third of fourth paper that referenced it? Like I said, several are paywalled, but from what I could piece together the sample size of the one you referenced was just under 200, the upper bounds was 94%, and I couldn't tell if this was in the paper citing your paper, or from your paper, but that children's faces had a 40% accuracy rate with. I found that funny because that's worse than chance. I'll try again to dig it out.
EDIT: Found it. What's the Difference between Men and Women? Evidence from Facial Measurement which appears to be V.Bruce citing her own work.
Human subjects are able to identify the sex of faces with very high accuracy. Using photographs of adults in which hair was concealed by a swimming cap, subjects performed with 96% accuracy. Previous work has identified a number of dimensions on which the faces of men and women differ. An attempt to combine these dimensions into a single function to classify male and female faces reliably is described. Photographs were taken of 91 male and 88 female faces in full face and profile. These were measured in several ways: (i) simple distances between key points in the pictures; (ii) ratios and angles formed between key points in the pictures; (iii) three-dimensional (3-D) distances derived by combination of full-face and profile photographs. Discriminant function analysis showed that the best discriminators were derived from simple distance measurements in the full face (85% accuracy with 12 variables) and 3-D distances (85% accuracy with 6 variables). Combining measures taken from the picture plane with those derived in 3-D produced a discriminator approaching human performance (94% accuracy with 16 variables). Performance of the discriminant function was compared with that of human perceivers and found to be correlated, but far from perfectly. The difficulty of deriving a reliable function to distinguish between the sexes is discussed with reference to the development of automatic face-processing programs in machine vision. It is argued that such systems will need to incorporate an understanding of the stimuli if they are to be effective.
The method of using the text preview cut out "human performance (94% accuracy with 16 variables)" which is actually describing the accuracy of the discriminant function they created. Human accuracy was 96%. Or in other words around what Thermal guessed in isolation with confounding variables removed. Those variables might support true positives, or like my hair, lead to more false positives. Your cite doesn't appear to measure that, focusing very closely on measurements.
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