Breaking the cycle: A systems analysis of maltreatment, power, \nand inequity in Canadian sports
Bibliographic record
Abstract
Reports of abuse in sports continue to emerge in the news alongside increasing calls from athletes for systemic change. Recent research and news stories highlight the continued and widespread prevalence of maltreatment across the sports system. The problem has been explored over the past several decades by athletes, researchers, and coaches among others with many recommendations for improvements being made. Despite positive strides, the problem persists. \n \nBuilding on the existing body of work, the following research explores the persistence of maltreatment and inequity in Canadian sports. Asking the question how might we reconsider power to build a safer, more equitable sports system, I examine the structures and influences that contribute to the problem. I examine public cases of abuse and first-hand perspectives to identify the relationships and primary sources of power shaping stakeholder behaviours. These insights are used to uncover opportunities to rethink the current power distribution and identify influential leverage points for change. It concludes by exploring an ideal future and providing strategic recommendations to move towards it.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".