Bibliographic record
Abstract
Male-dominated and sex segregated elite professional and amateur sport1 in North America constitutes a "sport nexus" (Burstyn, 1999; Heywood & Dworkin, 2003) that combines economic and cultural influence to reinforce and perpetuate gender injustice. The sport nexus is an androcentric sex-segregated commercially powerful set of institutions that is highly visible and at the same time almost completely taken for granted to the extent that its anti-democratic impetus goes virtually unnoticed. The sport nexus’s hegemonic role in defining sporting norms (Coakley & Donnelly, 2004) means that its role in shaping lower level amateur and recreational sporting institutions and cultures is highly significant. Fraser (2007) defines gender justice, and hence democracy, in terms of "participatory parity," that is, material and cultural equality for women. The sport nexus itself is characterized by highly gendered occupational segregation (Coventry, 2004). It further contributes to gender injustice, homophobia and transphobia by promoting the ideology of the two sex system (Fausto-Sterling, 2000) and gendering citizenship as fundamentally male (Burstyn, 1999). Feminist strategies for sport reformation attempt to reduce or eradicate the role of the sport nexus in legitimating and perpetuating gender injustice. In this article I consider the potential of these strategies and conclude with a set of recommendations for transforming organized sport at both elite and recreational levels.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".