Multiple Identities in a Marginalized Culture
Bibliographic record
Abstract
This article is a theoretical and empirical examination of female youth culture in recreation/drop-in centers. The authors attempt to integrate theories of female participation in leisure and sport with more mainstream perspectives on female youth subcultures. A gender-sensitive, cultural studies-based perspective emerges, underscored by a (Chicago-style) symbolic interactionist approach to understanding social process. Research findings from an ethnographic study of female youth in one such center in southern Ontario, Canada, are presented, with particular attention to how the various beliefs, behaviors, and customs that characterized female youth culture in the center were created, maintained, and referred to as the basis for interaction. The study findings showed that experiences within the center, although generally positive, were varied and extremely gendered, with female youth marginalized in the informal, male-dominated sport culture. Moreover, the findings revealed that among these youth, there existed simultaneously a resistance to broader, gender-and class-based limitations on sport participation and a reproduction of informal power structures. The relevance of these findings to theoretical understandings of female youth culture and youth-centered organizations and to practical and strategic approaches to programming for “at-risk” female youth are assessed, and suggestions for future research in this sparse area are provided.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".