What the reference describes.
In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in a biased sample of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected. If this is not accounted for, results can be erroneously attributed to the phenomenon under study rather than to the method of sampling. Medical sources sometimes refer to sampling bias as ascertainment bias.
What the process still cannot guarantee.
A large sample can be precise yet systematically unrepresentative.
That is a design criticism of how this research operation may be used, not a claim that the encyclopedia endorses the limitation. In this domain, the general redesign question is: human and machine distortions move from behavioral advice into enforceable evidence-lineage constraints.
Replace the mechanism.
Link sampling plans to population models and estimate transport uncertainty.
Implementation requires a typed scientific claim, explicit operational definitions, controlled access to evidence, an immutable record of relevant transformations, and independent checking appropriate to the kind of assertion. An AI-generated interpretation without those checks would reproduce the underlying failure at greater speed.
What would demonstrate improvement?
Use shifted population benchmarks to test generalization claims.
Compare with a defined baseline under matched resources, keep evaluation cases independent of the system under test, and measure both false alarms and undetected errors. Publish any negative or inconclusive result as part of the same investigation record.
Continue across concepts.
Each related title has its own revision-specific Wikipedia source and a separate critical dossier. Crosslinks are exploratory; they do not imply the encyclopedia articles support the proposed replacement.
No single authority.
The reference article establishes the historical and methodological subject under examination. The proposed criticism and replacement must earn their own support through reproducible tests and independent validation. Record disagreements instead of silently overwriting them.
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