Miracle Miles, Gender Verification and the Golden Age of Track and Field: Looking Beyond Equity in Elite Athletics in Canada and Abroad
Bibliographic record
Abstract
In 1954, Roger Bannister became the first man to run a mile in under four minutes. Scholars have since identified Bannister’s run as the most significant event in the golden age of track and field. This article explores the various ways we commemorate this era, and maps the intersections between these celebrations, gender verification, inequities in elite track and field, the presence of mythic barriers (that is, time barriers that athletes strive to surpass, and when they do, this becomes important to the history of that sport) in athletics, and the inscription of geopolitical concerns onto the bodies of female athletes. While these phenomenon may seem relatively unrelated, placing gender verification and mythic barriers in conversation with our ideation of track and field’s golden age reveals the racist and sexist scripts that continue to inform elite athletics. This article is guided by two central arguments. First, imagined athletic barriers are male-centred, which erases the accomplishments of female runners, a situation that is reinforced by inequities such as unequal prize money and promotion for female runners. Second, liberal feminist interventions such as demands for equal prize money, promotion, and mythic barriers that women can also attempt to surpass will not lead to equity for female athletes. Rather, equity is only possible if the termination of all forms of gender verification accompanies these strategies. Otherwise, the athletics oval will never become a safe space for women to challenge the imagined limits of their ability.
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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 | 0.000 | 0.000 |
| 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".