Drugs and democracy : in search of new directions
Bibliographic record
Abstract
In 1988 the United States Congress passed laws declaring improbably that the USA would be 'drug free' by 1995. In 1998 the United Nations General Assembly Special Session on Drugs committed itself to the implausible goal of eradicating the trade in heroin and cocaine within a decadeandmdash;at a time when global heroin production had trebled and global cocaine production had doubled. Somewhere in Australia, almost every year for the past quarter-century, there has been a royal commission or other major official inquiry into the illicit drug industry. The Australian government spends millions of dollars on attempting to control the illicit drug trade. Almost 85 per cent of these funds are allocated to law enforcement; 5 per cent goes to treatment and 10 per cent to prevention and research. Meanwhile the drug industry in Australia grows bigger and richer every year, and as a result our rates of addiction, crime and death continue to rise. Drugs and Democracy examines Australia's unsuccessful attempts to control the illicit drug industry, and discusses howandmdash;within the confines of our liberal democratic values and cultureandmdash;we could improve our strategies.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".