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Record W2911377445 · doi:10.1002/leap.1224

Is the drive for reproducible science having a detrimental effect on what is published?

2019· article· en· W2911377445 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.

Bibliographic record

VenueLearned Publishing · 2019
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsNoveltyCriticismMovement (music)Computer scienceEpistemologyProcess (computing)PublishingScientific progressEngineering ethicsData sciencePolitical sciencePsychologyLawPhilosophySocial psychologyAesthetics

Abstract

fetched live from OpenAlex

This paper is a critique of the part played by the reproducible research movement within the scientific community. In particular, it raises concerns about the strong influence the movement is having on which papers are published. The primary effect is through changes to the peer review process. These not only require that the data and software used to generate the reported results be part of the review but also that the novelty criterion should be deprecated. This paper questions a central tenet of the movement, the idea of a single, well‐defined, and iterative scientific method. Philosophers, historians of science, and scientists alike have argued extensively against the idea of a single method. Some going as far as to suggest that there are as many methods as scientists. I am convinced that there are broad, high‐level ideas that bind scientists together. Yet, anything more sharply delineated that could reasonably be entitled a scientific method is not logically or historically justified. If this criticism is accepted, then changes to the peer review process are not warranted. Furthermore, I would contend that the influence the reproducible research movement is having on the publishing of papers, and elsewhere, should be considerably curtailed.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Reproducibility · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualhigh
gptMetaresearch
Domain: Reproducibility · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.312
metaresearch head score (Gemma)0.175
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Scholarly communication, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.3120.175
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.005
Science and technology studies0.0010.000
Scholarly communication0.0900.019
Open science0.0070.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.486
GPT teacher head0.494
Teacher spread0.008 · 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