Reshaping Australian drug policy: the dilemmas of generic medicines policy
Bibliographic record
Abstract
With this edition, Australia New Zealand Health Policy publishes four articles on the theme of Australian and international generic medicines market dynamics and policy dilemmas. Changes soon to be introduced to pricing arrangements under Australia's Pharmaceutical Benefits Scheme (PBS) make this focus particularly topical. Beecroft presents a community pharmacy perspective on these issues. Faunce and Lexchin explore the vexed issue of 'evergreening' in Australia and Canada, with a comparative emphasis on the implications of bilateral trade agreements between these countries and the US. In a second article, Faunce investigates the generics sector from an industrial renewal perspective, arguing that it would be perilous to fail to develop a systematic approach to the promotion of this industry grounded in public good considerations. The present author provides an analysis of international generics markets which highlights the rise of competitive Indian suppliers.
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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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".