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Record W4385278485 · doi:10.31234/osf.io/758dx

L’importance de la science ouverte en recherche en psychologie

2023· preprint· fr· W4385278485 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

Venuenot available
Typepreprint
Languagefr
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La crise de réplication scientifique que le domaine de la psychologie traverse en ce moment remet en question la réputation de notre discipline et notre confiance dans une majorité de recherches passées et présentes. Le présent article couvre les points les plus importants en lien à la crise de réplication et la science ouverte, via une brève revue de littérature. Deux causes principales de la crise de réplication en psychologie ressortent : les pratiques de recherche douteuses et le manque de transparence. Heureusement, la science ouverte, qui met au cœur de sa démarche la transparence, la reproductibilité et les bonnes pratiques de recherche, permet d’adresser ces deux problématiques directement. Celle-ci recommande notamment : (a) le préenregistrement de l’étude; (b) le rapport enregistré; (c) la mise en ligne publique des données désidentifiées; (d) la mise en ligne des matériels et de la syntaxe; (e) l’utilisation de logiciels libres tels que R; (f) la prépublication; et (g) la publication en libre accès. Cet article couvre brièvement ces différentes pratiques.

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
gemmaOpen science
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptOpen science
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models splitAgreement 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)0.715
metaresearch head score (Gemma)0.384
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.332
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.7150.384
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0010.006
Science and technology studies0.0000.001
Scholarly communication0.0040.000
Open science0.0180.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0370.052

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 head0.935
GPT teacher head0.658
Teacher spread0.277 · 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