Favoriser la diffusion de la recherche dans diverses langues et cultures: Travailler au-delà des modèles occidentaux et anglocentriques
Bibliographic record
Abstract
En effet, la communaute mondiale en ergotherapie peut et doit travailler en collaboration afin de promouvoir les valeurs communes sous-jacentes de la profession; par exemple, le droit de tous les individus, communautes, groupes et populations a s’engager dans des occupations signifiantes ou a l’habilitation de leur participation occupationnelle en ayant acces a des services justes et equitables et en evoluant dans des milieux justes et equitables (p. ex., Townsend et Polatajko, 2013). Pour etre indexees, ce qui est requis pour faire une demande de facteur d’impact au Journal Citation Reports, ces revues doivent demontrer que les articles qu’elles publient sont largement cites, et ce, dans des revues publiees en anglais. Toutefois, recemment, ces revues sont passees a la publication bilingue en ajoutant des manuscrits en langue anglaise et, dans certaines situations, comme pour le Brazilian Journal of Occupational Therapy (BrJOT; http://www.cadernosdeterapiaocupacional.ufscar.br), en publiant des articles dans trois langues. (Ont.), OTR, OT(C) Redactrice en chef adjointe / Coredactrice Revue canadienne d’ergotherapie Ana Ana Paula Serrata Malfitano, PhD, OT (Bresil) Redactrice en chef, Brazilian Journal of Occupational Therapy Professeure, Federal University of Sao Carlos, UFSCar, Sao Carlos, Sao Paulo, Bresil
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.144 | 0.167 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.011 | 0.029 |
| Scholarly communication | 0.033 | 0.023 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".