Bibliographic record
Abstract
On 26th November the Australian Bureau of Statistics (ABS) published its population projections from the base year 2012 to 2101.1 Perhaps they chose this date to stall those mind-numbing conversations about when a new century begins. The ABS presented three scenarios for low, medium and high growth based on different assumptions about fertility, life expectancy and migration all of which are subject to a range of human, social, economic and environmental uncertainties. The ABS headlines were based on the medium growth scenario (projection B). By 2040, when the current cohorts of health students are in mid-career, Perth will have overtaken Brisbane in the population stakes with 3 million people and the Australian Capital Territory will have more people than Tasmania unless Treasurer Joe Hockey is more successful than his predecessors in cutting the public service. In 2053 Melbourne and Sydney will have 7.9 million people each if the projection holds. By this time the number of people aged over 65, with or without superannuation, is expected to double from 3.2 to 6.8 million and those aged over 85 are expected to triple to1.2 million and make up 4% of the population. In areas other than capital cities, fertility is assumed to be higher and mortality similar. About a quarter of the population will be living outside capital cities in the middle of this century. Rural health is defined by an interest in place and is not the chief focus of this analysis by the ABS city dwellers. One reason for this assumption is the less than flattering use of the phrase “balance of state” to refer to that part of the state other than the capital city. Nevertheless, these projections raise a number of interesting questions for those of us living in or with an interest in rural Australia. We could start by asking where these will people live and follow up by inquiring who will care for them. Will we still be using the same service models in 2040 in which we wait for people to develop symptoms and then muster the forces of specialist and curative medicine to heal them? How will our life expectancy change and in particular our disability-free life expectancy? Will we see an increase in retirement age or the age at which superannuation pensions become available? How will our population age-structure change and what will be the ratio of working to dependent populations? One last question, will our actions to address diet, exercise and broader health literacy make any difference? The ABS projections raise an important and longstanding challenge about the relationship between public or population health and curative health and related services. There may be more information by the time this editorial is published but we are awaiting further news about the federal government's intentions for Medicare Locals and particularly their role in rural communities. They have completed needs analysis studies of their populations, developed new services to fill some of the gaps identified, and are acting as a significant service provider in many rural communities. Some observers suggest that an incremental approach is likely which might include a change of name. Recent announcements of closures in manufacturing and concerns about budget shortfalls suggest that new funds will be in short supply. A more radical approach would be to clarify the roles and responsibilities for rural population health and the contributions of primary care, community health and institutional services. Population health expertise is located in state health services and Medicare Locals but is it sufficient, does it work collaboratively and can it influence the pattern of services delivered by private providers, the public sector, voluntary organizations and other arms of government such as education, housing and employment services? Population projections are accompanied with considerable uncertainty but even conservative estimates are cause for some concern. In the Australian Journal of Rural Health we regularly publish research and evaluation studies about new services or responses to emerging health problems. Publications that focus on future scenarios raise two further questions: can we scale up the many small, local and effective innovations that are taking place and if we do will such developments meet the needs generated by population growth and changes in population structure in rural Australia.
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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".