Bodies, borders, and Caster Semenya: geocorporeality and the disciplinary work of imaginary geographies
Bibliographic record
Abstract
The sex and gender status of elite athlete Caster Semenya has been the focus of much public debate concerning the legal and semantic boundaries of women’s bodies and of the need to create a ‘level playing field’ for women athletes. While biomedical, human rights, feminist and other scholarly perspectives have contributed to the ongoing discussion regarding the legitimacy of Semenya’s participation, as well as that of other athletes with ‘anomalous’ bodies, this paper draws from Said’s and Gregory’s theorisations of imaginary geographies to examine the ways in which elite athletic spaces are constructed and protected, as well as the bodies which are (dis)allowed into those spaces. Broadening the conversation with a geocorporeal framework can offer tentative ways forward in the current impasse regarding the inclusion of intersex athletes in elite competition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".