Australia: government subsidises long term care by up to £22000 a year
Bibliographic record
Abstract
The federal government is largely responsible for funding residential care for old people in Australia, helped by a combination of flat user fees and income tested fees. Care homes for elderly people (known as “aged care homes”) can charge up to ${type:entrez-nucleotide,attrs:{text:A66000,term_id:4537990,term_text:A66000}}A66000 (£25300; $38000; €39000) a year to look after a high care resident, with the government paying a subsidy of up to ${type:entrez-nucleotide,attrs:{text:A57500,term_id:3713365,term_text:A57500}}A57500 (£22000) and the elderly person making up the difference, in what are known as “basic daily care fees.” Residents thus contribute about 13% of the cost of their accommodation and care from their private income, savings, and pension. Those who do not have the full means tested pension may also have to pay an income tested fee, and high care residents with enough assets could also have to pay an accommodation charge. High care patients with sufficient assets and income are expected to contribute a quarter of the cost of their accommodation and care.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.075 | 0.025 |
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".