Hurry hard!: Exploring the possibilities and pitfalls for curling to help (re)build society in/through community sport
Bibliographic record
Abstract
Amid the well-documented fraying of society, community spaces where people from diverse social locations share time and space are increasingly rare, yet necessary. Participation in curling, a sport known for its sociability, is increasing around the world and receiving growing scholarly interest. In this conceptual paper, we briefly synthesize extant literature related to curling in order to explore how its qualities can help facilitate the (re)building of community and society. We then present recommendations for future curling scholarship to understand and advance curling’s place in society. More specifically, we offer four thematic streams to build upon previous curling research while charting new directions, which broaden our collective understanding about the relationships between curling, community (sport) spaces, and leisure. We conclude by offering insights for leisure and community sport scholars to address the ongoing polycrisis in/through curling and their own areas of focus. Together, these understandings offer great potential to help (re)build society.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.018 | 0.030 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".