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Record W2978101249 · doi:10.1017/s0140525x18000912

Holding replication studies to mainstream standards of evidence

2018· letter· en· W2978101249 on OpenAlexaff
Duane T. Wegener, Leandre R. Fabrigar

Bibliographic record

VenueBehavioral and Brain Sciences · 2018
Typeletter
Languageen
FieldMathematics
TopicAdvanced Causal Inference Techniques
Canadian institutionsQueen's University
Fundersnot available
KeywordsReplication (statistics)MainstreamPsychologyValue (mathematics)Cognitive psychologySocial psychologyStatisticsMathematicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Replications can make theoretical contributions, but are unlikely to do so if their findings are open to multiple interpretations (especially violations of psychometric invariance). Thus, just as studies demonstrating novel effects are often expected to empirically evaluate competing explanations, replications should be held to similar standards. Unfortunately, this is rarely done, thereby undermining the value of replication 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.452
metaresearch head score (Gemma)0.839
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.548
Threshold uncertainty score0.675

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4520.839
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0050.004
Science and technology studies0.0060.046
Scholarly communication0.0150.026
Open science0.0110.011
Research integrity0.0390.064
Insufficient payload (model declined to judge)0.0090.010

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 head0.687
GPT teacher head0.582
Teacher spread0.105 · 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

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReproducibility
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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