A significant portion of intellectual and professional circles now treat statistical disparity not merely as an accusation of discrimination, but as sufficient evidence to conclude that a particular outcome was caused by discrimination. The issue is not ignorance of statistical significance. The issue is misuse of statistics. Statistical disparity can raise a question; it cannot, by itself, answer who acted, why they acted, or whether a specific accused party caused a specific injury.

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The assertion you advance, though cloaked in the language of prudence, collapses upon inspection for want of both rigor and historical sensibility. It is neither novel nor particularly incisive to observe that statistical disparity alone does not narrate the full chain of causation; yet to suggest that its evidentiary weight is therefore negligible betrays a misunderstanding of how inference operates in both law and reason. Patterns, when persistent, robust, and resistant to alternative explanation, do not merely “raise questions”—they furnish compelling prima facie evidence that demands rebuttal, not dismissal. To insist upon direct, individualized proof in every instance is to ignore the very purpose for which statistical reasoning was refined: to illuminate systemic forces that evade anecdotal detection. Your argument, then, sets an impossible evidentiary bar, one that would render many forms of discrimination effectively unprovable, and in so doing, it substitutes skepticism for substance without offering any credible countervailing framework.

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Correlation and causation are different concepts. Both can be measured clearly, but they are not interchangeable. Using correlation as a substitute for causation is a fraudulent distortion of evidence.

Y’all both use a lot of highfalutin words to argue badly.

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Not even bullshitting in this bowl is safe from the AI invasion anymore.

Me: Please draft a response arguing against the points made in the attached.

Chat GPT: ….

Me: Thanks, please redraft the response to make it more catty and in bad faith.

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