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Record W7099393458

Health Issues, 2004, Number 79, pp. 19-24. 1 From A Fairer Medicare to Medicare Plus: What are the Implications for the Future of Bulk-billing and Medicare?

2003· article· en· W7099393458 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsCommonwealthFalling (accident)Quarter (Canadian coin)General practiceMedicare Part BHealth economics
DOInot available

Abstract

fetched live from OpenAlex

The recent passing by the Senate of the Commonwealth government’s Medicare Plus package, followed a year-long debate about the future of Medicare. During this period a Senate Select Committee on Medicare was established to examine the government’s first package, A Fairer Medicare, and then reconvened to consider its second package, Medicare Plus. This article examines both packages and explores the impact that Medicare Plus will have, if any, on the rate of bulk-billing and patient out-of-pocket costs for general practitioner services throughout Australia and asks whether ‘Medicare Plus’ will strengthen or undermine Medicare. The Decline in Bulk-billing by General Practitioners The decline in bulk-billing and rise in out-of-pocket costs for general practitioner services in recent years has led to a significant focus on health policy, and specifically Medicare. Bulk-billing rose from 74.2 % in 1992-93 to a peak of 80.6 % in 1996-97 (see figure 1) before falling to 66.5 % in December 2003 (Commonwealth Department of Health & Ageing, 2004a). During this same period, out-of-pocket costs for general practitioner services have risen from an average of $6.90 to $14.03 (Commonwealth Department of

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)0.002
metaresearch head score (Gemma)0.007
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.112
Threshold uncertainty score0.375

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0090.004
Open science0.0010.001
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.1120.035

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 head0.049
GPT teacher head0.313
Teacher spread0.265 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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