Bibliographic record
Abstract
Acknowledgements Notes on Contributors Introduction P.Markula Reading Media Texts in Women's Sport: Critical Discourse Analysis and Foucauldian Discourse Analysis J.Liao & P.Markula Opening up the Gendered Gaze: Sport Media Representations of Women, National Identity and Racialized Gaze in Canada M.MacNeill From 'Iron Girl' to 'Sexy Goddess': An Analysis of the Chinese Media P.Wu 'Acceptable Bodies': Deconstructing the Finnish Media Coverage of the 2004 Olympic Games P.Markula Double Trouble: Kelly Holmes, Intersectionality and Unstable Narratives of Olympic Heroism in the British Media L.Hills & E.Kennedy Different Shades of Orange?: Media Representations of Dutch Women Medallists A.Elling & R.Luijt Winning Space in Sport: The Olympics in the New Zealand Sports Media T.Bruce Heroes, Sisters and Beauties: Korean Printed Media Representation of Sport Women in the 2004 Olympics E.Koh An Analysis of AmayaValdemoro's Portrayal in a Spanish Newspaper During Athens 2004 M.Martin The Media as an Authorizing Practice of Femininity: Swiss Newspaper Coverage of Karin Thurig's Bronze Medal Performance in Road Cycling N.Barker-Ruchti Reproducing Olympic Authenticity: Representations of 2004 'Olympic Portraits of U.S. Athletes to Watch' N.Spencer
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.019 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 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".