Bibliographic record
Abstract
Ice hockey holds a revered position in Canadian culture, renowned for fostering national pride and camaraderie. However, in recent years, the hockey environment has come under scrutiny due to the resurgence of assault and discrimination cases. These incidents have raised concerns, particularly regarding the psychological and physical well-being of youth involved in the sport. Consequently, parents, administrators, fans, and politicians have begun questioning existing practices and advocating for change. This study takes a unique approach to address these concerns, using foresight and systems thinking methods in collaboration with youth hockey players and leadership. The aim is to identify strategies that can effectively transform Canadian youth hockey culture, making it more inclusive, equitable, and sustainable. By involving a diverse group of youth hockey players, coaches, administrators, and stakeholders in interviews, the research gives voice to the experiences, challenges, and aspirations of young athletes, empowering them to shape the future of their sport. A crucial component of the paper leverages foresight and systems thinking methods to visualize the current state of hockey's ecosystem, the various future states plausible within a 10-year horizon, and the highest-yielding interventions to create the most sustainable change. The findings of this study provide a comprehensive framework for action, offering policymakers, sports organization leaders, parents, and concerned citizens a series of reflection prompts and resources to advance youth hockey culture in their realms of influence. These insights can inform the development of policies, the design of programs, and the decision-making processes, all with the goal of effecting transformative change in the Canadian hockey landscape.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.015 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".