L’approche communicationnelle en études du jeu : un apport des chercheur.se.s de la Faculté de communication de l’UQAM
Bibliographic record
Abstract
Les études du jeu ont récemment été développées par des chercheurs.e.s issu.e.s de différentes disciplines ayant chacune leurs concepts, leurs approches et leurs méthodologies de prédilection. Cet article décrit comment les chercheur.se.s en études du jeu de la Faculté de communication de l’Université du Québec à Montréal (UQAM) ont contribué à l’institutionnalisation de ce domaine de recherche dans la francophonie, de même qu’au développement d’un cadre conceptuel, épistémologique et méthodologique propre aux études du jeu dans le champ de la communication. Après avoir situé leurs travaux dans la constellation des études sur le jeu, cet article présentera les postulats de leur approche communicationnelle, les différents types de communication pouvant être étudiés dans le cadre de recherches portant sur le jeu, ainsi que les plans d’analyse correspondant aux potentiels terrains d’études.
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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 | 0.033 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.014 | 0.019 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".