Falsification-First Stress Test

Falsification-First Stress Test

Core question: Where have we fooled ourselves — and is each load-bearing claim even falsifiable?

This campaign is a deliberate inversion of publication-oriented stress testing. In a publication frame, the artifact is a thing to be defended; success = it survives debate and gets hardened. That frame optimizes for persuasiveness and is actively dangerous for truth-seeking research: it rewards a claim for being un-attackable, which is exactly the failure mode of an unfalsifiable theory. Here the artifact is a suspect. We WANT to break it, because breaking it teaches us something true and cheap (compute/thought) before we spend expensive effort (sandbox, wet-lab) on a false premise. Confidence is not assumed and defended down; it is EARNED up, only by surviving honest assault.

Stance (operator-set, non-negotiable)

• 证伪优先, 不摁死 (falsification-first, not execution). The goal is diagnostic: surface flaws WE overlooked, not manufacture a verdict that kills the work for sport. A successful attack revises the map or demotes a claim; it does not "win." A failed attack (the claim survives) is also a real result — corroboration — provided the attack was severe (Mayo: a claim is corroborated only to the degree it passed a test it would probably have failed if false).
• No hardening. Finding a weakness NEVER triggers "patch it to look stronger." It triggers exactly one of: (a) revise the claim, (b) demote the claim's status, (c) record it as honest residue. Patching-to-survive is the patchwork anti-pattern this whole project rejects.
• Unfalsifiability is the worst outcome, not the best. A claim no attack can touch is not strong — it is empty. Flag it RED and demote to conjecture/analogy.

Three outcome buckets (the only verdicts)

Every load-bearing claim exits in exactly one bucket:

Methodology Sources

• Popper (1959) — Falsificationism: a theory's content = what it forbids; seek the forbidden.
• Lakatos (1976) — Proofs and Refutations: counterexamples force claim refinement, not abandonment; monster-barring vs. concept-stretching.
• Mayo (1996, 2018) — Severe testing / error statistics: a passed test corroborates only if it was severe (would likely have failed if the claim were false).
• Platt (1964) — Strong inference: for each claim, design the experiment whose alternative outcomes exclude hypotheses.
• Meehl (1990) — Risky predictions; the difference between a theory that predicts and one that merely accommodates.

Strategy Routing (by artifact type)