Bibliographic record
Abstract
In theCommission of Inquiry into the Use of Drugs and Banned Practices Intended to Increase Athletic Performance(Dubin 1990), commissioned by the Canadian government in the aftermath of the infamous Ben Johnson drug scandal at the 1988 Seoul Summer Olympic Games, Chief Justice Charles Dubin stated that the problem of drug/substance use represented the single greatest moral crisis in high‐performance sport today. His statement was prescient in that there is probably no other issue that is seen by either the general public or authorities in major sport organizations to be a greater threat to the integrity of international sport than the use of banned drugs/substances. Certainly no other issue warrants the same commitment of resources and bureaucratic effort, especially since the creation of the World Anti‐Doping Agency in 1999, which now oversees anti‐doping efforts worldwide. The problem of drug use in sport also presents for sociologists and those in related academic disciplines in sports studies an opportunity to study the deviant subculture of drug use, the social and political dynamics of modern sport, and even more generally to explore the sociology of deviant behavior and the social construction of “normal” and “pathological” categories in a major sphere of social life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".