Anti-Bullying Policies in Canadian Sport: An Absent Presence
Bibliographic record
Abstract
In Canada, it is estimated that one-third of bullying occurs outside of educational settings, including sport and recreation spaces (Shannon, 2013). Beyond important academic literature on abuse in athlete-coach relationships, however, there is little research on peer-to-peer bullying in sport. This is a noticeable absence considering assertions that there is a high potential for bullying to occur (Kerr, Jewett, MacPherson, & Stirling, 2016; Shannon, 2013). Moreover, bullying has been connected to children and youth drop-out rates (Fraser, 2015).Our interest in this project was to determine how Canadian national sport organizations (NSOs) address peer-to-peer bullying through policy. Although antibullying strategies that rely solely on policy are ineffective (Short, 2013), clearly communicated and implemented policies remain important (Mountjoy et al., 2016; Olweus & Limber, 2010; Walton, 2004). Thus, we focused our analysis on policy documents available to the public on NSO websites.A total of 118 documents were retrieved, consisting of various codes of conduct and harassment policies. Of these 118 policy documents, only three had been produced that addressed peer-to-peer bullying specifically. In the remaining 115 documents, bullying was mentioned just 19 times and only defined in five documents. The absence of specific policy and policy statement addressing peer-to-peer bullying is important to highlight. Well-written and implemented policies are needed in order to help create safer spaces in sport for children and youth. More specifically, it is imperative for sport and recreation organizations to have clearly defined policies on peer-to-peer bullying, which are openly communicated to members of the organization. It is also important for organizations to make it clear how members should report incidents of bullying.Finally, policies that adequately define bullying and that address its root causes such as sexism, racism, ableism, and LGBTQphobia are considered best practice as they are determined to be more complete. Policies that highlight the root or ideological causes of bullying may have more long-term impact on reducing bullying behaviours and incidents, as children and youth are encouraged to embrace difference and demonstrate empathy, respect, and compassion (Short, 2013). These policies should co-exist with educational programs on bullying, such as those offered by Respect in Sport and the Canadian Red Cross.Subscribe to JPRA
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".