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Record W3046007858 · doi:10.1177/1088868320931366

A Validity-Based Framework for Understanding Replication in Psychology

2020· review· en· W3046007858 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePersonality and Social Psychology Review · 2020
Typereview
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsReplication (statistics)Construct validityExternal validityPsychologyConcurrent validityIncremental validityInternal validityConstruct (python library)Criterion validitySocial psychologyTest validityValidityPredictive validityCognitive psychologyPsychometricsComputer scienceClinical psychologyInternal consistencyStatisticsMathematics

Abstract

fetched live from OpenAlex

In recent years, psychology has wrestled with the broader implications of disappointing rates of replication of previously demonstrated effects. This article proposes that many aspects of this pattern of results can be understood within the classic framework of four proposed forms of validity: statistical conclusion validity, internal validity, construct validity, and external validity. The article explains the conceptual logic for how differences in each type of validity across an original study and a subsequent replication attempt can lead to replication "failure." Existing themes in the replication literature related to each type of validity are also highlighted. Furthermore, empirical evidence is considered for the role of each type of validity in non-replication. The article concludes with a discussion of broader implications of this classic validity framework for improving replication rates in psychological research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.728
GPT teacher head0.641
Teacher spread0.087 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it