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Record W114765731 · doi:10.22374/jptcp.v11i1.62

A PERSPECTIVE ON AUSTRALIA’S NATIONAL MEDICINES POLICY

2019· article· en· W114765731 on OpenAlexvenueaboutno aff
Susan E. Tett

Bibliographic record

VenueJournal of Population Therapeutics and Clinical Pharmacology · 2019
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsInterdependenceEquity (law)Medical prescriptionAgency (philosophy)Perspective (graphical)Health careQuality (philosophy)BusinessPolitical sciencePublic relationsPublic administrationMedicineEconomic growthEconomicsPharmacologySociology

Abstract

fetched live from OpenAlex

There is international interest in Australia's health care system for prescription medicines. The issue is particularly topical in Canada with the debate following publication of the Romanow Report into the future of health care in Canada. This Report recommended a new National Drug Agency. Australia has a National Medicines Policy with four arms-quality, safety and efficacy of medicines; equity of access; a viable and responsible pharmaceutical industry; quality use of medicines. The four arms of the Policy are interlinked and interdependent for optimal functioning. In this paper, an overview of how the prescription drug system in Australia works is presented. The manuscript focuses upon specific aspects of the Policy, describing how it functions and some of the processes integral to success, from the viewpoint of the author. The discussion includes some of the advantages of Australia's system for pharmaceuticals as well as some of the problems, as these present opportunities for development and change.

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)0.005
metaresearch head score (Gemma)0.006
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.157
Threshold uncertainty score0.312

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0060.005
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0100.009
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 head0.595
GPT teacher head0.680
Teacher spread0.085 · 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
GenreCommentary

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

Citations3
Published2019
Admission routes2
Has abstractyes

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