Doping use among young elite cyclists: a qualitative psychosociological approach
Bibliographic record
Abstract
Using a psychosociological approach, the purpose of this study was to identify and understand the use of doping substances by young elite cyclists. Semi-structured interviews were conducted with young cyclists who were hoping to find a professional team and cyclists who had recently become professional. All of the young cyclists interviewed took nutritional supplements and believed that they improved their performance, which has been shown by other scholars to be a risk factor for doping. These cyclists believed that doping at the professional level in cycling was acceptable but did not approve of it at the amateur level. They were attracted to doping; they were open to using doping substances themselves if it was the key to continuing their cycling career, but only after they became professional. Team staff, doctors, parents and friends helped to create a "clean" environment that prevented the young cyclists from doping before becoming professional. The more experienced cyclists, who doped or used to dope, transmitted the culture of doping to the young cyclists, teaching them doping methods and which substances to use. This study could help to improve prevention and help to detect doping, as it is clear that doping behaviors begin at the amateur level.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".