Due for review: 2017 Supporting older Australians Background
Bibliographic record
Abstract
Australians are living longer. This is due to a number of medical and social factors that have resulted in reduced infant mortality, fewer young people dying in motor vehicle accidents and fewer older men dying from heart disease.1 On average, Australian males born in in 2007-09 will live to 79.3 years, and females to 83.9 years, an increase from 47.2 years and 50.8 years respectively in 1881-1890.2 Presently, Aboriginal and Torres Strait Islander people have lower life expectancy compared to non-Indigenous Australians3, and Closing the gap has been identified by the Council of Australian Governments as a priority in health policy. Likewise, the number of older Australians and the proportion of the population who are aged over 65 years are also increasing – there are nearly 2.7 million Australians between the age of 65-84 years and more than 415,000 over the age of 85 years in 2011.4 This is due to a number of factors such as population growth, changes in birth rates, and death rates falling for conditions such as cancer, cardiovascular disease, chronic obstructive pulmonary disease, asthma and injuries.5 The Australian Bureau of Statistics projects the total number of Australians above the age of 65 years is projected to increase exponentially to more than 6 million by 2051. The Productivity Commission in its report on Caring for Older Australians estimates that by that same time, over 3.5
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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 teacher head, 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".