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Record W3111116449 · doi:10.47678/cjhe.vi0.188799

L’influence perçue des instruments d’action publique fédéraux et provinciaux sur la production de recherche universitaire au Canada

2020· article· fr· W3111116449 on OpenAlexaffvenueabout
Olivier Bégin‐Caouette, Silvia Mirlene Nakano Koga, Grace Karram Stephenson

Bibliographic record

VenueCanadian Journal of Higher Education · 2020
Typearticle
Languagefr
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversity of TorontoUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPsychologyArt

Abstract

fetched live from OpenAlex

Cet article vise à comparer la perception qu’ont les professeurs de Colombie-Britannique, d’Ontario et du Québec des instruments d’action publique fédéraux et provinciaux quant à leur influence sur la production de recherche dans leur province. Les scores moyens, une MANOVA et des analyses post-hoc de Dunnett C réalisées sur les résultats provenant d’un questionnaire distribué à 786 participants révèlent que les instruments fédéraux sont perçus comme ayant une influence plus importante que les instruments provinciaux, mais aussi qu’il existe une différence significative entre les scores attribués aux instruments provinciaux par les professeurs québécois et par leurs homologues des autres provinces.

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)0.013
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.987
Threshold uncertainty score0.288

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.002
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.278
GPT teacher head0.456
Teacher spread0.178 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainIncentives
GenreEmpirical

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
Published2020
Admission routes3
Has abstractyes

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