Fallacies: M (Part 3 of 3)

Core idea

The final run of M entries is anchored by the full-moon myths — and they make the topic's sharpest point. People believe a full moon drives madness, crime and births, yet study after study finds nothing. The explanation is not the moon; it is the observer. A nurse who expects strange behavior on full-moon nights writes more notes on those nights; the quiet nights leave no record. Psychiatrists call this illusory correlation: we remember the hits and erase the misses, so a pattern appears that was never there.

Around this sit smaller corrections — milk does not really make mucus, though it feels like it does; moths do not eat clothes, their larvae do; black is not the universal color of mourning. The unifying idea is that perception is not a clean instrument. We see what we expect, we remember selectively, and folk wisdom is often just that bias passed down as fact.

Why it matters

The full-moon entry matters because the believers include professionals — police, nurses, psychiatrists — whose judgments affect real outcomes. When a belief is propped up by selective memory rather than evidence, even experienced people can be confidently wrong, and they will keep finding "confirmation" because their attention is doing the confirming.

The smaller entries matter as a reminder that folk wisdom is a mixed inheritance. Some of it is sound; much of it is a fossilized error. "Murder will out" is comforting but false — truth emerges only when someone has the wit and energy to drag it into the light. Believing it does so on its own is a recipe for letting things slide. And the milk-and-mucus entry is a neat case of a placebo of the senses: whole milk coats the mouth, the coating feels like mucus, and the feeling outvotes the measured data.

Key takeaways

Mental model

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Practical application

The skill to take from this batch is auditing your own memory before trusting a pattern. The full-moon believer is not lying — they genuinely recall wild nights. The flaw is that the calm nights left no trace. Before claiming "X always happens when Y," ask whether you have actually counted the times Y happened and X did not.

Example

A manager insists deployments always break on Fridays and bans Friday releases. Apply the M topic's audit. The manager vividly remembers several Friday failures — but did they count the Fridays that went fine, and the Tuesdays that broke? Pull the actual incident log: if failures are spread evenly across weekdays, the Friday pattern is illusory correlation, kept alive because a Friday outage ruins the weekend and is therefore unforgettable, while a smooth Friday vanishes from memory. The fix is not a Friday ban; it is counting the non-events that the manager's memory quietly discarded.

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