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   @polarisera reposted your post (polarisera@spinster.xyz)'s status on Monday, 10-Mar-2025 04:18:17 JST @polarisera reposted your post

   It's called Bayes' theorem, and we have study after study demonstrating doctors are too retarded to get it, and commit malpractice almost daily.

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     lainy (lain@lain.com)'s status on Monday, 10-Mar-2025 04:18:17 JST lainy

     in reply to
     @polarisera i read this and thought of you: https://statmodeling.stat.columbia.edu/2025/03/08/a-post-mortem-on-the-gino-case-committing-fraud-is-right-now-a-viable-career-strategy-that-can-propel-you-at-the-top-of-the-academic-world/
     
     "The incentives for fraud in business academia are significant. If you can meet the standards for hiring, promotion, and tenure at an R1 university (something that is much easier once you fabricate your data), you will get:
     – A 6-figure salary with full benefits until you retire
     – Complete job security
     – A flexible work environment (no boss, remote work…)
     – The social status and reputational benefits that go with the “Professor/Dr.” title
     – Opportunities to do book deals, TED talks, to teach in executive education, to conduct corporate workshops…
     The benefits of fraud must be balanced with the risks of course. Are the risks of being caught for faking data high enough? I [Ziani] don’t think so:
     
     The peer review process, as it exists today, makes it extremely difficult to catch fraud. . . .
     
     The bar to accuse someone of fraud is extremely high. Failing to replicate the effect? Not enough. Non-sensical effect sizes? Not enough. Anomalies in data? Not enough. Unless you can invest the resources to identify anomalous patterns of fraud across multiple papers, THEN drum up enough support from journals or universities to consider your suspicions, THEN hold their feet to the fire when they are unwilling to act… the probability that the person will never face consequences for fabricating data is very high.
     
     The incentives to investigate and call out fraud are non-existent. In fact, the opposite is true: If you find something fishy in a paper, your mentor, colleagues, and friends will most likely suggest that you keep quiet and move on (or as I have learned the hard way, they might even try to bully you into silence). If you are crazy enough to ignore this advice, you are facing a Sisyphean task: Emailing authors to share data (which they do want not to), begging universities to investigate (which they do not want to), convincing journals to retract (which they do not want to), waiting months or years for them to share their findings with the public (if it ever happens)…"