An Intersectional Analysis of the Recruitment and Participation of Second-Generation African Canadian Adolescent Girls in a Community Basketball Program in Ottawa, Canada
Bibliographic record
Abstract
Guided by the experiences and perspectives of sport practitioners, in this paper, an intersectional lens was used to examine age, gender, race, socioeconomic status, and religion and how they relate to the recruitment and participation of second-generation, low-income, African Canadian, Black Muslim, and Christian adolescent girls in a community-based basketball program in Ottawa, Canada. Semistructured interviews were conducted with 11 program coordinators and coaches involved in the City of Ottawa Community Centre Basketball League (CCBL), and reflexive thematic analysis of the data was engaged. The findings were threefold: (a) CCBL coordinators and coaches recognize the importance of representation to enhancing their support to program users; (b) CCBL coaches and coordinators make efforts to build trust with and increase buy-in from first-generation immigrant parents to improve girls’ program participation; and (c) CCBL coaches and coordinators make religious accommodations in response to the needs of Muslim and Christian program users. The findings illustrated that community-based sport programs serving second-generation African Canadian adolescent girls in low-income communities require multifaceted program and outreach strategies that consider the intersecting social experiences of participants to improve recruitment and participation. To conclude, policy and program design and implementation strategies to support the creation of inclusive, equity-driven community-based sport practices were proposed.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.021 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".