[학술논문] Adolescent sport, recreation and physical education: experiences of recent arrivals to Canada
Bibliographic record
Abstract
This paper explores the perceived benefits and challenges of sport, recreation and physical education participation of culturally diverse adolescent girls and boys who are recent arrivals to Canada. The aim of the research was to further our understanding of the attitudes and experiences of English as a second language (ESL) students. Following from the Ethnicity and Public Recreation Participation Model (Gómez, 2002 Gómez , E. (2002) The Ethnicity and Public Recreation Participation Model , Leisure Sciences , 24 (2) , 123 – 143 . \n[Taylor & Francis Online], [Web of Science ®], , [Google Scholar] \n), we examined the language acculturation, sub-cultural identity and perceived discrimination of ESL students, as well as the perceived benefits and challenges to participation in physical education, sport and recreation. To that end, a questionnaire was completed by 87 upper-level ESL students, and focus group interviews were conducted with a further sub-sample of 40 students, from three metropolitan schools. Drawing on both sets of data, we discuss how perceptions of benefits, challenges and other considerations interplay with gender, ethnicity and participation in sport, recreation and physical education. \n(출처: Taylor & Francis Online, \nhttps://doi.org/10.1080/13573320500111770)
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".