« De lâinterculturel de valeurs à lâinterculturel de faits », entretien croisé avec Jacques Proulx et Tania Ogay
Bibliographic record
Abstract
Dans cet entretien, Tania Ogay, professeure en sciences de l’éducation à l’Université de Fribourg (Suisse), et Jacques Proulx, professeur de psychologie à l’Université de Sherbrooke (Canada), nous livrent quelques réflexions sur la spécificité, les apports et les défis de la recherche interculturelle, en lien avec leurs expériences et pratiques respectives. Nous avons profité de la présence de ces deux chercheurs reconnus au XIIIe congrès de l’Association internationale pour la recherche interculturelle (ARIC), qui s’est tenu à l’Université de Sherbrooke du 19 au 23 juin 2011, pour les réunir et prendre le temps d’échanger sur ce thème à la fois flou et d’une urgente actualité.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.131 | 0.037 |
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".