Funding Victoria's public hospitals: the casemix policy of 2000-2001
Bibliographic record
Abstract
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
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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 | 0.020 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 0.005 |
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".