Searching for Paralympians: Characteristics of Participants Attending “Search” Events
Bibliographic record
Abstract
Initiatives have been designed to attract novice athletes and to enable transfer for experienced athletes. However, the authors have very little knowledge of the effectiveness of these programs. To further improve our understanding, this study explored the demographic and sporting careers of 225 participants attending one of the 10 Paralympian Search events held between 2016 and 2018. The sample consisted of participants with a wide range of impairments and sport experiential backgrounds. The majority of the participants reported having some experience in sports, suggesting that either the promotions reached athletes involved in sports already or the advertising appealed especially to this cohort. Athletes with impairments acquired at various stages of their lives (congenital, before adolescence, adolescence, early adulthood, and adulthood) displayed differences in their sporting trajectories, suggesting considerations for current developmental models. Furthermore, it should be considered to vary the testing locations of future events to increase the reach to rural areas and implement new methods to attract novice participants.
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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".