Leisure research amid socio-political unrest: A reflection on struggle in turbulent times
Bibliographic record
Abstract
This essay offers a reflection on the relevance of leisure amidst current social unrest and the ways in which scholars thinking through leisure can attend to discussions part of social movements and radical resistances. This paper interrogates the ways leisure is bound up in socio-political tension through its direct link to capitalism, labour, and reproduction of the status quo while, simultaneously, being part of the action needed to resist such harms, necessary for our analyses as leisure scholars. As we continue to reflect on TALS’s ‘New Leisure Studies’ panel (2021) and Mowatt’s sensibility in considering, ‘what is “leisure” in the midst of [this socio-political] landscape?, we feel that in these challenging times, more critical analysis, openness, connectedness, and creativity is required to reflect the nuanced and interconnected social dynamics of leisure more fully.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".