Un demi-siècle de recherche en loisir au Canada : entretien avec Gilles Pronovost
Bibliographic record
Abstract
The year 2025 marks the 50th anniversary of the initial Canadian Congress on Leisure Research (CCLR), held in the city of Quebec in 1975. Gilles Pronovost, one of the original organizers, was interviewed by François Gravelle during the 17th Congress in May 2023 at the University of Ottawa, themed “A Half Century of Canadian Leisure Research: Towards a More Inclusive Future.” The conversation explored the origins of leisure studies in Quebec and Canada, the founding of the journal Loisir et société/Society and Leisure, the origins and development of the Canadian Leisure Studies Association and the CCLR, as well as Pronovost’s reflections on the field’s future and his advice to emerging researchers. This article presents a revised and expanded version of that interview.
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 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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.048 | 0.022 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 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".