The McKinsey study that claimed diverse workforces lead to bigger profits was always fake (they won't share data, it doesn't replicate for the S&P500 or other settings, and it doesn't make sense).
But fake social psych research is a demand problem, not just a supply problem.
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But fake social psych research is a demand problem, not just a supply problem.
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Typical Saturday evening in the university, the 3 pre-med students have a shootout (in the dorm—shooting through the neighbor's walls) aiming in the direction of the mechanical engineers, who disrespected them about their SAT exam.
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Some UK users on the YouTube subreddit are reporting that their VPNs are being detected and blocked by the platform
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Men focus on external, inter-group fighting
Women focus on internal, intra-group fighting
Coalitions and conflict: A longitudinal analysis of men's politics, 2021
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Women focus on internal, intra-group fighting
Coalitions and conflict: A longitudinal analysis of men's politics, 2021
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Ever notice stuff like
“Why are broke guys so good in bed?”
or
“Why are the hottest people so boring?”
It feels like there’s a tradeoff between traits, but that’s often an illusion.
What’s really happening is this -- when you filter for people who score high on the sum of two traits (e.g. total dating appeal), you start to see a negative correlation between those traits within that group, even if no such tradeoff exists in the broader population.
It’s a statistical artifact. You’re looking at people who made the cut overall.
The plot attached shows it --
Looks and coolness are uncorrelated in the population, but once we filter for people with high "total attractiveness" (looks + coolness), a negative correlation emerges.
This doesn’t just apply to dating, it shows up anytime you’re selecting based on the total of two uncorrelated or loosely related traits.
🄳🄾🄾🄼🄿🤖🅂🅃🄸🄽🄶
“Why are broke guys so good in bed?”
or
“Why are the hottest people so boring?”
It feels like there’s a tradeoff between traits, but that’s often an illusion.
What’s really happening is this -- when you filter for people who score high on the sum of two traits (e.g. total dating appeal), you start to see a negative correlation between those traits within that group, even if no such tradeoff exists in the broader population.
It’s a statistical artifact. You’re looking at people who made the cut overall.
The plot attached shows it --
Looks and coolness are uncorrelated in the population, but once we filter for people with high "total attractiveness" (looks + coolness), a negative correlation emerges.
This doesn’t just apply to dating, it shows up anytime you’re selecting based on the total of two uncorrelated or loosely related traits.
🄳🄾🄾🄼🄿🤖🅂🅃🄸🄽🄶
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