Naked Waneek Horn-Miller: Incredible performances call for reinterpretation
Bibliographic record
Abstract
At the eve of the Summer Olympics in 2000, images of women athletes in the media were numerous. Where people might have expected action shots of these athletes, the burst of coverage was dedicated to women athletes who had decided to pose naked. In Canada, Waneek Horn-Miller, assistant captain of the Canadian women's water polo team, posed naked for the cover of Time magazine. Was the cover promoting Horn-Miller's sexuality, sensuality and femininity more than her athletic skills and abilities? How was the media constructing Horn-Miller's experience of posing naked? How was she, herself; constructing her experience? What identities was she performing on the cover? A semiotic analysis of the Time cover as well as a qualitative analysis of 10 newspaper articles and an interview conducted with Horn-Miller suggested that, rather than supporting and promoting dominant discourses of femininity, gender and race, the picture offered a challenge to those discourses and forced the viewers to think of the naked body of Horn-Miller in terms of new language and new vocabulary. Furthermore, my poststructural interpretation revealed that, while the media have strategically constructed their texts to assign Horn-Miller with a singular, fixed and unified "feminine-looking-woman-athlete" subjectivity mainly influenced by the dominant femininity discourse, Horn-Miller's speech highlighted how she performed fluid, fragmented and contradictory identities that were influenced by the adoption of various subject positions in different discourses, notably the femininity, sport and Native discourses.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".