“I feel more Canadian with hockey.” Identity and Belonging via Ice Hockey in a Diverse Canada
Bibliographic record
Abstract
This paper explores the relationship between the participation in organized ice hockey by immigrants and racialized minorities (compared to those born in Canada and who are white) and their sense of national identity and sense of belonging to Canada. A Bourdieusian theoretical framework is utilized to conceptualize hockey in terms of a field, habitus, and cultural and symbolic capital. The argument is made that hockey is Janus-faced and a contested terrain with a tension between exclusion and inclusion whereby human agency is vitally important. Yet the hockey arena and engagement in the game, either as players or fans or in some other capacity, provides a multicultural common space potentially enabling an interactive pluralism amongst diverse communities. The data are derived from qualitative semi-structured interviews with hockey players, fans and key informants in Calgary and Toronto. Overall, the findings show that for most immigrants and racialized minorities engaged in organized ice hockey, there is more likely a sense of Canadian national identity and a sense of belonging to Canada compared to the Canadian-born and to whites. These findings further add to the value of making hockey more inclusive via equity, diversity and inclusion policies and initiatives.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.012 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".