"I started noticing this bigger gap": How feelings of difference impact sport competence among young people living in neighborhood improvement areas
Bibliographic record
Abstract
Sport involvement is suggested to offer a context for health and wellness, civic engagement, economic development and prosperity, and other physical, psychological, and social benefits (Canadian Sport Policy, 2012; Fraser-Thomas et al., 2005); however, sport can also be a site for differentiating, marginalizing and excluding individuals and groups (Spaaij et al., 2014). This study explored the lived experience of sport participation among 16 youth and young adults living in Neighborhood Improvement Areas within Toronto. Recognizing that culture is fundamental to an individual's experiences, behaviours, and identity, we utilized a cultural praxis framework, which combines blended theory, lived culture, and social action (Blodgett et al., 2015). Specifically, we adopted a narrative inquiry approach guided by the principles of community-based research (e.g., Conrad & Campbell, 2005). Findings indicate that feelings of difference (e.g., body, skills, opportunities) influenced perceptions of sport competence, which in turn affected sport participation outcomes (e.g., drop-out, poor performance, and resilience). Participants often expressed feelings of difference in the context of geography, ethnicity and gender. Findings are discussed through the lens of Harter's (1978, 1982) Competence Motivation Theory and Cultural Studies Framework (Fisher et al., 2003). This research suggests that broader contextual issues need to be considered when exploring sport competence and motivation for sport participation. Specifically, findings highlight the importance of acknowledging feelings of difference in sport contexts, creating more welcoming sport environments for all youth and young adults, increasing access and opportunities, and enhancing perceptions of competence.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".