Introduction to Special Issue. ‘A half century of Canadian leisure research: towards a more inclusive future’. Papers from the Canadian Congress on Leisure Research 17
Bibliographic record
Abstract
2025 marks the 50th anniversary of the first Canadian Congress on Leisure Research (CCLR). This special issue contains papers presented at CCLR17, the most recent CCLR which was held at the University of Ottawa in May, 2023. The theme of CCLR17 was ‘A half century of Canadian leisure research: Towards a more inclusive future’. Reflective of CCLR17’s theme that focused on inclusion, unlike previous CCLR special issues that were published in only one of Canada’s leisure journals, this special issue is being published in both Leisure/Loisir and Loisir et Société/Society and Leisure with six papers being published in each journal. The first paper in each journal, each based on a banquet keynote talk, focuses on the first half of the conference theme: ‘A Half Century of Canadian Leisure Research’. The remaining five papers in each journal focus on the second half of the conference theme: ‘Towards a More Inclusive Future’.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.163 | 0.070 |
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".