Home ownership as a (crumbling) fourth pillar of social insurance in Australia
Bibliographic record
Abstract
This paper examines the potential that asset based welfare has to protect households from poverty after retirement by focusing specifically on the role of home ownership in maintaining average living standards and preventing poverty among older Australians. Incomes and housing costs are compared between Australia and six other nations (Canada, UK, USA, Italy, Finland and Sweden) and the likely future trends in Australia examined. Though asset-based welfare has the potential to ease the fiscal constraints faced by the state, it may well lead to poorer social insurance outcomes for households with limited saving capacity over their lifetime. Access to home ownership tends to be more limited than access to the labour market and fluctuations in asset prices can lead to arbitrary shifting of wealth between generations. Social insurance programs can be more readily designed with explicit distributional objectives. By international standards, the older population in Australia has a low average income and a high income poverty rate. However, unlike most other rich nations, more than 80 per cent of people over retirement age in Australia own their own home. After taking account of their lower housing costs, their average living standard and after housing poverty rate is similar to that in the other countries. Nonetheless, the Australian model means that those who miss out on home ownership are multiply disadvantaged and projections suggest that this group will grow in size in the coming decades.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".