Risk and the public right to know: Case studies of psychoactive drug prescribing patterns in British Columbia
Bibliographic record
Abstract
PharmaNet data shows marked variations in prescribing rates for psychoactive drugs across British Columbia and thus indicates potential risk to public health. Analysis of primary data obtained under Freedom of lnformation from the Ministry of Health's prescription database identified geographic and demographic prescribing extremes for antidepressants, stimulants and sedatives over 12 months ending July, 2003. From a medical perspective low rates indicate some patients who might benefit are untreated. High rates may indicate some patients are unnecessarily exposed to the potential risk of harm from side effects and adverse drug reactions. Under B.C.'s Freedom of Information law, information indicating significant risk to health and safety must be made public. Psychoactive drug prescription data should be posted in same way data as data on other health hazards such as toxic contamination sites. Disclosure would warn doctors and patients, encourage analysis by experts and media, and promote public discourse on psychoactive drugs.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| 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".