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Record W2089540131 · doi:10.1071/hp070411

Reshaping Australian drug policy: the dilemmas of generic medicines policy

2007· article· en· W2089540131 on OpenAlexaboutno aff
Hans Löfgren

Bibliographic record

VenueAustralia and New Zealand Health Policy · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPharmaceutical Benefits SchemeHealth economicsPopulation healthPublic healthHealth policyPublic policyPublic relationsPharmaceutical policyPharmaceutical industryEconomicsPublic administrationPolitical scienceHealth careMedicineEconomic growthMedical prescription

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0060.009
Scholarly communication0.0100.008
Open science0.0020.004
Research integrity0.0120.008
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.174
GPT teacher head0.404
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2007
Admission routes1
Has abstractyes

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