‘Acceptable Bodies’: Deconstructing the Finnish Media Coverage of the 2004 Olympic Games
Bibliographic record
Abstract
Feminist sport studies scholars have examined the ideological construction of feminine identity in the Olympic media by comparing the coverage of women athletes in ‘masculine’ and ‘feminine’ sports. Feminist interest in this classification stems from the idea that in the current male-dominated culture of sport, it is more acceptable for women to participate in ‘feminine’ sports. Female participants in ‘masculine’ sports will be marginalised in the media coverage because they challenge the existing gender order in sport. At the same time, increased coverage of women in ‘masculine’ sports indicates resistant change to the ideological construction of sport. In this chapter, I analyse whether feminist research can challenge the current structure behind women’s sport media representation through readings of feminine and masculine sports. I use Jacques Derrida’s affirmative deconstruction to map the logic of sport classification in feminist sport studies. My discussion is based on two strategies (Patton, 2003): first, I trace the history of the concept of ‘acceptable sport’ in feminist sport studies; and second, I examine possibilities for changing theoretical understandings of women’s sport participation in contemporary society. To illustrate my discussion, I examine the types of sports in which women were represented in a Finnish newspaper during the Athens Olympic Games, 2004. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 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".