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Record W7100497153

Funding Victoria's public hospitals: the casemix policy of 2000-2001

2002· article· en· W7100497153 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
Topicdemographic modeling and climate adaptation
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Context (archaeology)MainlandPopulationState (computer science)Capital cityCapital (architecture)
DOInot available

Abstract

fetched live from OpenAlex

On 1 July 1993 Victoria became the first Australian state to use casemix information to set budgets for its public hospitals commencing with casemix funding for inpatient services. Victoria’s casemix funding approach now embraces inpatient, outpatient and rehabilitation services. The geographic and demographic context Victoria is the second most populous state in Australia, second only to New South Wales. Melbourne, the capital of Victoria, is the second largest city in Australia and boasts a cultural diversity unparalleled in any other Australian capital with almost 45 per cent of residents being born overseas or having a parent born overseas. Twenty per cent of Victorians come from countries where English is not the primary language. Victoria is the smallest mainland state (227,420 km2) constituting 2.96 per cent of the national landmass (Australian Bureau of Statistics 2000a). The estimated population at June 1999 was 4.71 million people, approximately one quarter of the Australian population, making Victoria the most densely populated of the states. The Victorian population grew at a rate of 1.2 per cent in the year to June 1999, compared with 0.6 per cent per year over the previous three years. The total population of Victoria is predicted to grow to between

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.496
GPT teacher head0.448
Teacher spread0.048 · 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 teacher head, not a consensus.

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

Citations0
Published2002
Admission routes1
Has abstractyes

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