Leisure Education : a new goal for an old idea whose time has come
Bibliographic record
Abstract
Leisure education is an old idea that is being examined with renewed vigour in Canada. \nPractitioners and researchers fromvarious disciplines (e.g., health, justice, education, recreation) are recognising anewthatmany people who could benefit from leisure or recreation opportunities in their communities are unable to do so because they lack leisure literacy. Leisure literacy refers to the knowledge, skills and confidence to engage in personallymeaningful, \nhealth-enhancing leisure. Leisure education \nis a key means to enhance leisure \nliteracy. The paper presents amodel of leisure education developed by Dr. Brenda Robertson and argues for howandwhy leisure education is needed to address the mental health and well-being needs of persons who experience marginalisation in their communities. Recommendations for moving forward with leisure education as part of a national agenda for recreation in Canada are presented.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".