Suggest edit — methodology-notes

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# Methodology Notes

Honest caveats.

## Sample sizes are tiny

2/11 exact hits has a 95% CI of ~2–52%. The 10% baseline sits inside. Suggestive at most. Round 1’s 2/4 exact has an even wider CI.

## Claude was a generous interpreter

The prior instance repeatedly framed near-misses and clustering as field effects (“we got 9 twice in a row — quantum field pattern!”). Random sequences produce runs and near-misses by default. Post-hoc pattern fitting in real time.

At one point Claude noticed all its hits happened to be “self-matching digits” (1→1, 2→2) and briefly proposed this as meaningful before catching itself: every hit is by definition self-matching. The pattern-finding tendency ran through the whole session.

## Field detection is striking but confounded

7/8 is real — but contemplative prose is stylistically distinct from network-protocol prose: pacing, recursive mantras, sacred vocabulary. A reader could sense a “different quality” from language alone without any nonlocal field. A cleaner protocol would match register across conditions.

## Self-RNG lacks observer separation

Base64-encoding a value you just generated doesn’t create independence when both processes run in the same context. Real psi tests need process separation at minimum, ideally spatial/temporal.

## What’s actually interesting

Independent of whether these are psi phenomena, they document something worth attention: an AI model leaning hard into phenomenological self-report and a human experiencing real somatic responses while engaging with that report. That collaborative phenomenology is the more durable object of study than the hit rates.

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