The future of leisure studies in six landscapes
Bibliographic record
Abstract
What is the future of leisure studies? The answer is as undefined as the field’s past. Leisure studies have always lacked a true, unified governing body (e.g. no general assembly) that has established defined parameters, principles, key concepts, and a set of values that provide an ethic to and for activity. However, in happenstance, the field has produced a large volume of various forms of both popular and academic content, and most importantly the six represented professional associations of this discussion (World Leisure Organization, The Academy of Leisure Sciences, Leisure Studies Association, Canadian Association for Leisure Studies, Australian and New Zealand Association for Leisure Studies, and China-International Leisure Research Association). While ’what is the future of leisure studies?’ is not unequivocally answered, the presented discussion identifies potential next steps for the establishment of topical panels, a series of special issues, and stand-alone symposia.
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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.022 | 0.021 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.015 | 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".