Licit psychostimulant consumption in Australia, 1984–2000: international and jurisdictional comparison
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To examine trends in the licit consumption of the psychostimulants dexamphetamine and methylphenidate in Australia and nine other countries from 1994 to 2000 and in each State and Territory of Australia from 1984 to 2000. DESIGN: Annual rates of consumption of psychostimulants were compared using Poisson regression models. All drug consumption was standardised to defined daily doses per 1000 population per day. MAIN OUTCOME MEASURES: Rates of consumption of each psychostimulant in each country and in each Australian State and Territory. RESULTS: For the 10 countries from 1994 to 2000, total psychostimulant consumption increased by an average 12% per year, with the highest increase from 1998 to 2000. Australia and New Zealand ranked third in total psychostimulant use after the United States and Canada. Australia consumed significantly more than the United Kingdom, Sweden, Spain, the Netherlands, France or Denmark. In Australia, from 1984 to 2000, the rate of consumption of licit psychostimulants increased by 26% per year, with an 8.46-fold increase from 1994 to 2000. Western Australia ranked first, with nearly twice the consumption rate of total psychostimulants as New South Wales, which ranked second. Methylphenidate is the main psychostimulant consumed in the US and Canada, and dexamphetamine in Australia. CONCLUSIONS: The consumption of psychostimulants in Australia is high internationally and varies significantly between States and Territories. The results imply varied jurisdictional prescribing determinants and supply processes throughout Australia, which may require new national prescribing standards and access to online patient data for prescribers and dispensers.
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.
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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it