Silent Evidence
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
The history and data we see are those that have 'survived' and been recorded. Those that failed, disappeared, or were never recorded (silent evidence), though numerous, are systematically ignored. This is more profound than survivorship bias because it points to unobserved history.
SCAFFOLDING EFFECT
Reduce cognitive load
The trap of visibility. When assessing risk, don't just look at 'what happened', imagine 'what could have happened but didn't' and 'what happened but wasn't recorded'. There are no biographers in the cemetery; the losers don't speak.
Anchor fast decisions
Observation samples are naturally biased towards 'survivors and those recorded'; the failed, disappeared, and unrecorded constitute the silent majority. This is more fundamental than survivorship bias: not only are 'winners overestimated', but even 'existence' is selectively erased, leading us to infer patterns from a distorted sample.
MINIMUM ACTION
In progress 0/2Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Silent_Evidenceverified
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