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snxwmp6
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how to explain gender based hatred in our society ?
Today, we're going to discuss what I believe is the biggest source of division in humanity
Lookism, social media, dating culture, and a whole range of psychological and social mechanisms have created the perfect environment for resentment to grow on both sides.
TABLE OF CONTENTS
I. The Algorithm Problem: Why Your Feed Is Not a Sample
II. Anecdotal Evidence and Its Limits
III. The Vocal Minority Effect
IV. Stated vs revealed preference
V. mate selection filters : hypergamy, heightism and lookism
VI. Evolutionary Psychology: Scope and Limits
VII. Conclusion
disclaimer : I'm not God and I may have made mistakes.I. The algorithm problem
• Everybody in this post already "knows" what women are like, or what men are like.
JFL.
Ask where that knowledge comes from and it's always the same retard answer :
•"because heightism"
•"because hypergamy"
•"because males are all potential predators"
In fact all those answers comes from social media, TikTok, a random clip, slop comments. That is not a sample. A sample is drawn at random from a population. Your feed is drawn from whatever you paused on last Tuesday.
• Recommender systems are designed for engagement, meaning watch time, repost, shares... NOT accuracy, NOT representativeness.
• And guess what ? hostility toward an out-group is excellent at generating engagement.
• An analysis of about 2.7 million posts found that posts about the political out-group were shared roughly twice as often as posts about the in-group, and each out-group term raised the odds of a share by 67%. That study is political, not gender-based. I'm using it because it measures the mechanism, and the mechanism doesn't care whether the out-group is a party or a sex.
source : mediawell
• Now the part that will make me unpopular with my own side but I dgaf. The claim "the algorithm radicalizes people" is weaker than all those iqlets pretends.
• In a randomized experiment on Facebook and Instagram during the 2020 US election, switching users to a chronological feed changed what they saw and how long they stayed, but did not significantly change polarization over three months.
• Different platform, different topic, and critics argue that Meta changed the feed during the experiment, which affects the control condition. So I'm not claiming a feed makes you hate anyone. I'm claiming it makes your sample garbage. That is a different claim, and only that one needs to be true for this post to work.
source : Princeton university / nsf.gov
And remember : it applies to both camps.
• The man who watches "women are all foids" TikToks and the woman who watches "men are evil" TikToks are running the same rigged experiment.
• The content from their own side saying the same bs ? Scrolled past in half a second, or filed under "it's just a joke".
Selective exposure + selective memory = congrats, you've been doing science with n=1 and a conflict of interest.
II. Anecdotal evidence and it's limit
• "B-b-but my experience..." Yes. Your experience is real. It is also one data point filtered by who you approach, who approaches you, what you tolerate, and what you remember.
• Tversky and Kahneman named the first problem in 1973: the availability heuristic. What comes to mind easily gets rated as common.
• Baumeister and colleagues (2001) reviewed the second: bad events outweigh equally intense good ones in memory and judgment. So one betrayal "but he / she played me" gets stored with a label "I hate males/ females", and a thousand boring, decent interactions get stored as nothing. Then you "count your evidence" and wonder why it all points the same way.
The rule cuts both ways : "My girlfriend is great, so you're wrong" is as retarded as "my ex gave me PTSD, so they're all like that".
disclaimer : I'm not saying your experience is fake. I'm saying it cannot be extrapolated to billions of people.III. The vocal minority effect
• Have you actually tought about who produces the slop content you're reading ?
• Pew found that about 80% of tweets from US Twitter users came from just 10% of users, who posted a median of 138 times a month, versus 2 for everyone else.
• Small group writes, huge group (you) reads. And the people with the strongest grievances are overrepresented in the small group, because people who have a loving girl/boyfriend and are rated HTN/B on .org don't post about it.
• Then there's the second layer: what each side believes the other side thinks.
• Studies on gender norms have found that both men and women can misjudge what the other side actually believes. In one set of preregistered studies, people underestimated how concerned men actually were about gender bias in STEM.
• So the same basic mechanism that people can't understand appears here:
what I think you think ≠ what you actually think.
And if both sides systematically overestimate the other side's hostility, we get a a self-sustaining and a self-reinforcing hatred.
source : pubmed
IV. Stated vs revealed preference
• Ask a man what he wants and he says "personality".
• Ask a woman and she says "kindness, humor, ambition".
Holy philosophy until Friday night comes and everyone needs to relief stress.
In Eastwick and Finkel's speed-dating study, participants reproduced the classic stated differences, but there were no sex differences in how attractiveness and earning prospects related to interest in real partners, and the ideals stated beforehand failed to predict who actually attracted them. A direct replication with 307 participants found the same thing: attractiveness and earning prospects raised interest, and gender didn't moderate it.
• People say what makes them look decent, and they often don't know what actually drives their choices in the first place. Psychologists have been saying that since the 1970s: people can lack introspective awareness of what influences their own judgments.
V. mate selection filters : hypergamy, lookism and heightism
Three words that have wrecked more comment sections than any real war on this fuckass app.
Every camp grabs one, cries about it
and assumes the other side lives in heaven.
Half of you genuinely think hypergamy only happen to men. The other half think lookism only happens to women. Both halves are wrong and crazy loud.
hypergamy
reminder to all of our iqlet :
• Half of you use "hypergamy" to mean "ugly girl + hot guy = holy hypergamy".
•That's not what the word says. The term goes back to the 1880s, when English anthropologists were studying Indian caste: it referred to a woman marrying into a caste at least as high as her own, and more broadly to any marriage with a partner of higher social status.
• Hypergamy and its opposite, hypogamy, were coined in the 19th century while translating classical Hindu law books. The axis is status. Class, caste, money, education. Nothing in the original definition says a word about your fucking PSL rate.
So we have actually two unfounded claims :
• aiming above your looks is a female hobby.
• men are the pure ones who love with their souls.
stop coping.
here are some proof
case 1 :
Researchers built fictitious dating profiles, varied their photo attractiveness and education, and had them send random invitations for a serious relationship to real online daters. Nobody knew they were in a study, so nobody had any reason to perform. Result: men and women both preferred attractive over unattractive profiles, regardless of their own attractiveness. Both. Equally on the looks axis, in the wild, with randomization.
case 2 :
The network data. In Bruch and Newman's analysis of a popular dating site, both sexes pursued partners about 25% more desirable than themselves, and the chance of a reply dropped as the gap grew. This is observed messaging behavior, not self-report (pre-shot to every person saying this).
Case 3 :
In a speed-dating replication with 307 participants, attractiveness and earning prospects raised romantic interest, and gender didn't moderate it. A meta-analysis pooling 97 studies leaned the same way for face-to-face situations. A separate analysis of dating-site activity logs (Taylor et al., 2011) reports that people sought contact with partners more attractive than themselves. So the "I don't care about looks" speech collapses at first contact, on both sides.
case 4 :
On OkCupid, men rated women on a fairly balanced scale, then ignored a lot of women they found reasonably attractive and piled their messages onto the top-rated ones.
Voici la suite, à coller après le case 4. La première image de ce lot est un doublon du case 4, je ne l'ai pas retranscrite deux fois. Texte d'origine conservé, fautes comprises.
heightism
To all my 5.4 manlets reading this : yes, women want tall men. In a sample of 650 students, women were more selective and more consistent than men about partner height, and were happiest with a partner about 21 cm taller, against 8 cm for men.
heightism and lookism
• But IRL the male-taller norm and a male-not-too-tall norm show up, but the effects are modest. Real life doesn't look like your dating app filter, and women on one dating site weren't interested in men more than about 17% taller than themselves.
• "Under 6ft = over" is just an excuse for you being high innhib lmao.
• to all my ladies reading this: if you're going to tell me you want a partner "at least 6ft" and also that men are shallow for wanting "a nice body", explain the math to me !dnr.
• Overall, both sides hate on each other for standards and expectations they both have.
VI. Real grievances
• The question of this post: does the gender war come from reality or from perception ?
• Here's the answer. Both sides have real problems and hate comes from how each side treats the other's because we are a low iq society that can't love each other.
Let me explain
- step 1 -
According to UN data, about 47,000 women and girls were killed by intimate partners or other family members in 2020. Women make up only a tenth of homicide victims in public, but in 58% of killings by partners or family members, the victim was a woman or girl.
The fear matches that: in Gallup's 2025 survey of over 145,000 adults in 144 countries, 67% of women worldwide said they feel safe walking alone at night against 78% of men. In the US it's 58% of women against 84% of men, and gaps of at least 10 points showed up in 104 of the 144 countries. So to all my moids, you need to sybau when a girl is telling you she feels unsafe in the streets or with someone.
- step 2 -
• In the US in 2022, the male suicide rate was 23.0 per 100,000 against 5.9 for women, three to four times higher across two decades. And in 2022, 17% of men reported receiving mental health treatment in the past year against 29% of women.
• with a death gap like that, it looks like a group that gets less help, not one that needs less. So to all my foids, when you say "men's mental health does not matters" you should learn to sybau.
- step 3 -
Both conclude the other side doesn't care. In a 2024 US survey, only 42% of young men believed young women understand the problems men face, and 72% of young women felt young men don't understand theirs. Feeling dismissed then gets read as hostility.
VII. Conclusion
If you've read all of this, it's because you're tired. Tired of being hated, or tired of hating. Good. That's the only qualification this post required.
You have understood every components of this useless hatred.
and now there is only one single thing to do : learn to love each other.
- sources -
Baumeister, R. F., Bratslavsky, E., Finkenauer, C., & Vohs, K. D. (2001). Bad is stronger than good. Review of General Psychology, 5(4), 323–370.
Bruch, E. E., & Newman, M. E. J. (2018). Aspirational pursuit of mates in online dating markets. Science Advances, 4(8), eaap9815.
Collins English Dictionary. "Hypergamy" (via Dictionary.com).
Egebark, J., Ekström, M., Plug, E., & van Praag, M. (2021). Brains or beauty? Causal evidence on the returns to education and attractiveness in the online dating market. Journal of Public Economics, 196, 104372.
Fry, R., Aragão, C., Hurst, K., & Parker, K. (2023). In a growing share of U.S. marriages, husbands and wives earn about the same. Pew Research Center.
Gallup (2025). Global Safety Report 2025.
Garnett, M. F., & Curtin, S. C. (2024). Suicide mortality in the United States, 2002–2022. NCHS Data Brief No. 509, CDC.
Guess, A. M., et al. (2023). How do social media feed algorithms affect attitudes and behavior in an election campaign? Science.
Hamermesh, D. S., & Biddle, J. E. (1994). Beauty and the labor market. American Economic Review, 84(5), 1174–1194.
Hitsch, G. J., Hortaçsu, A., & Ariely, D. (2010). What makes you click? Mate preferences in online dating. Quantitative Marketing and Economics, 8(4), 393–427.
Moore-Berg, S. L., Ankori-Karlinsky, L.-O., Hameiri, B., & Bruneau, E. (2020). Exaggerated meta-perceptions predict intergroup hostility between American political partisans. PNAS, 117(26), 14864–14872.
Nisbett, R. E., & Wilson, T. D. (1977). Telling more than we can know: Verbal reports on mental processes. Psychological Review, 84(3), 231–259.
Panchal, N., & Lo, J. (2024). Exploring the rise in mental health care use by demographics and insurance status. KFF.
Rathje, S., Van Bavel, J. J., & van der Linden, S. (2021). Out-group animosity drives engagement on social media. PNAS, 118.
Stulp, G., Buunk, A. P., Pollet, T. V., Nettle, D., & Verhulst, S. (2013). Are human mating preferences with respect to height reflected in actual pairings? PLoS ONE, 8(1), e54186.
Survey Center on American Life (2024). Why young people feel misunderstood by the opposite sex.
Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207–232.
UNODC (2021). Killings of women and girls by their intimate partner or other family members: Global estimates 2020.
Wang, W. (2014). Record share of wives are more educated than their husbands. Pew Research Center.
Witmer, J., Rosenbusch, H., & Meral, E. O. (2025). The relative importance of looks, height, job, bio, intelligence, and homophily in online dating: A conjoint analysis. Computers in Human Behavior Reports, 17, 100579.
Wojcik, S., & Hughes, A. (2019). Sizing Up Twitter Users. Pew Research Center.
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