The Academic Achievement of Elite Athletes at an Australian University: Debunking the Dumb Jock Syndrome
Bibliographic record
Abstract
Elite athletes and their academic achievement in higher education have long been subject to considerable debate within North American scholarship. This interest proliferated especially after the release of the Knight Report (2001), which, amongst other findings, revealed a clear negative link between elite athletes and their academic achievement. While sport has always had a long and prominent presence in Australian higher education, both sport and education scholars have given very little attention to this area. To rectify this neglect, this study investigates the academic achievement of elite athletes (N=313) at an Australian university and compares their results to the general student population in the 2012 academic year. Using both qualitative interviews (n=20) and quantitative secondary data analysis, the findings suggest that despite heavy sporting commitments and necessarily demanding training timetables, the sampled elite athletes performed at levels equal to, or superior to, their peers. In particular they show a lower failure rate. These findings are discussed in relation to student abilities, education program management and the challenges faced in terms of elite athlete stereotyping.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".