Incomplete Induction
Updated 2026-08-09
INTRODUCTION
English translation pending.
CORE DEFINITION
A form of inductive reasoning that derives a general conclusion from a limited set of observations. Its core proposition is that since the observed sample is always smaller than the domain it covers, the conclusion is probable rather than necessary, and the assumption of nature's uniformity is itself an inductive claim. The qualifier is that this does not make induction useless; it makes scientific conclusions provisional best guesses open to counterexamples.
SCAFFOLDING EFFECT
Reduce cognitive load
- Sample check: ask how many cases the conclusion actually rests on and how they were chosen. - Confidence label: mark inductive conclusions as probable rather than certain in your own notes. - Counterexample hunt: actively search for the case that would overturn the generalization.
Anchor fast decisions
Every inductive conclusion generalizes beyond what has been observed, so the inference adds content that no amount of data can guarantee. This is why a single counterexample can destroy a generalization that thousands of confirming cases supported, and why the rational response is to hold the conclusion while continuing to test it.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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- wiki.mbalib.comhttps://wiki.mbalib.com/wiki/%E4%B8%8D%E5%AE%8C%E5%85%A8%E5%BD%92%E7%BA%B3%E6%B3%95verified
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