traaaaaaannnnnnnnnns
Welcome to /c/traaaaaaannnnnnnnnns, an anti-capitalist meme community for transgender and gender diverse people.
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Please follow the Hexbear Code of Conduct
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Selfies are not permitted for the personal safety of users.
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No personal identifying information may be posted or commented.
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Stay on topic (trans/gender stuff).
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Bring a trans friend!
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Any image post that gets 200 upvotes with "banner" or "rule 6" in the title becomes the new banner.
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Posts about dysphoria/trauma/transphobia should be NSFW tagged for community health purposes.
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When made outside of NSFW tagged posts, comments about dysphoria/traumatic/transphobic material should be spoiler tagged.
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Arguing in favor of transmedicalism is unacceptable. This is an inclusive and intersectional community.
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While this is mostly a meme community, we allow most trans related posts as we grow the trans community on the fediverse.
If you need your neopronouns added to the list, please contact the site admins.
Remember to report rulebreaking posts, don't assume someone else has already done it!
Matrix Group Chat:
Suggested Matrix Client: Cinny
https://rentry.co/tracha (Includes rules and invite link)
WEBRINGS:
🏳️⚧️ Transmasculine Pride Ring 🏳️⚧️
⬅️ Left 🏳️⚧️🏳️🌈 Be Crime Do Gay Webring 🏳️⚧️🏳️🌈 Right ➡️
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If it makes you feel better, I watch a few shorts from a woman who talks about talking through your relationship problems to make it healthier instead of mining it for clout on TikTok and immediately I got a flood of right-wing MRA type videos
The reason Youtube is getting absolutely fucking demolished by tiktok is that tiktok actually serves you recommended content that is like what you engage with and actually watch whereas Youtube recommends you the exact fucking opposite.
nah they both have documented issues funneling people towards fascist content.
the notion of the recommendation algorithm is inherently flawed, especially in the absence of standards or moderation. you're always going to be using metrics that are poor proxies for actual interest.
Agreed. Expressed vs revealed preference is the devil in the details of building useful recommendation models that seems to always have this catch. It’s worsened by a hugely unaccounted for spread of experience among users. Anyone training models daily takes for granted the often subtle but unusual ways they’re careful to avoid miscommunicating preferences. Slow-scrolling past content without pausing to lessen interest capture weighting, for example, or using statistically associated concepts for steering. Neither is average user behavior, yet developers often assume it.
In the end, did the user actually tell you their preference? or did you simply attempt to give them one [at any cost]
YouTube recommendations are like gifts from an inattentive spouse but somehow way worse. It’s like if you said “I love dogs” and your spouse was like “I know you love dogs so I gathered up all the uncollected dog shit in the neighborhood and put it in the front seat of your car.”