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Single Study Generalization

Also Known As: Single-study over-reliance Replication neglect
Aspect ID: single_study_generalization

Definition

Single study generalization is the error of treating one study's findings as definitive evidence, without requiring replication or considering the base rate of true effects in the research area. Given publication bias, underpowering, and researcher degrees of freedom, any single study has a substantial probability of being a false positive.

Examples

A single neuroimaging study with 30 participants reports that a mindfulness intervention physically changes brain structure. News headlines declare 'Mindfulness proven to rewire the brain.' Subsequent larger studies fail to replicate the specific structural finding.

A single study conducted on 45 American college students finds that people make better decisions when they need to urinate. Tech blogs immediately run headlines: 'Scientists discover full bladder boosts decision-making.' The finding has never been independently replicated across different populations or settings.

One small trial in a single Danish town finds that installing blue streetlights reduces nighttime crime by 30%. City councils across Europe begin purchasing blue lighting systems based solely on this one study, before any replication in different urban environments or crime contexts has been attempted.

Verification Steps
Verification Steps
Binary yes/no questions that an AI must answer to detect a reasoning pattern in a text.
Each of the 452 aspects has verification steps — simple yes/no questions designed to systematically detect whether a pattern appears in a text. For ad hominem: "Does the argument attack a person rather than their claim?" For false dichotomy: "Are only two options presented when more exist?" This ensures consistent, reproducible analysis.

Binary (yes/no) questions an LLM must answer to identify this aspect:

  1. 1

    Is a conclusion being drawn from a single study without referencing replication evidence?

    Type: binary
  2. 2

    Does the study have a sample size large enough to provide stable estimates?

    Type: binary
  3. 3

    Has the finding been independently replicated in at least one other research group?

    Type: binary
  4. 4

    Does the study's population, setting, and methodology generalize to the claim being made?

    Type: binary
Deep Dive
The expandable detail section on each aspect page with examples, psychology, and counter-strategies.
The Deep Dive section provides in-depth information about each aspect: a real-world example showing the pattern in action, an explanation of why it works psychologically, practical advice on how to counter it, alternative names, and links to related aspects.