I just published a book with a chapter on navigating glitches: deja vu, synchronicity, the moments reality stutters. Writing it forced me into a problem this sub lives with every day, and I want to put it to you straight, because the book ended up printing the problem as an open flag instead of pretending to solve it.
The boring explanation gets right of first refusal. Littlewood's back-of-envelope: an ordinary person encounters tens of thousands of small events a day, so a one-in-a-million event should land about once a month (Littlewood, A Mathematician's Miscellany, 1953; the per-month framing popularized by Freeman Dyson). Miracles are a calendar feature. And deja vu can be reliably induced in the lab: when a new scene shares its underlying layout with an old one you cannot consciously recall, familiarity fires without its source attached (Cleary, Current Directions in Psychological Science, 2008). So the null hypothesis is well armed.
Here is the part that matters for simulation theory. Even if some stutters are signal, render artifacts, seam lines, whatever your preferred model calls them, the noise floor above guarantees false positives at a fixed rate. Which means glitch reports are worthless as evidence without a discrimination procedure: a test, a threshold, some credential that separates the monthly Littlewood coincidence from an actual anomaly. I looked for one while writing and could not find one I would defend, so the book prints the hole in its own text, marked GAP: the taxonomy identifies kinds, not credentials.
The practical rule the chapter lands on is deliberately fail-safe: treat any glitch as one vote, never a verdict, and act only on what you would defend without the glitch. If the coincidence points at calling your sister, the call was defensible anyway. If it points at emptying your savings, the glitch was never entitled to move that much. Run that way, you cannot be badly wrong whether the stutter was signal or noise. But fail-safe is not the same as informative, and this sub is the room most likely to have thought hard about the informative version.
So the question: does anyone here have, or know of, a serious attempt at a discrimination procedure? Statistical tests on personal coincidence logs? Predictions a simulation hypothesis makes about glitch clustering that pure noise does not make?
Disclosure, because it bears on whether you trust any of the above: the book was written in extensive collaboration with an AI and says so on its copyright page. Every claim in it carries a marker separating established results, like the two citations here, from the book's own speculation. Not linking anything. This is the question, not an ad.