World Bank The Australian Annuity Market
Bibliographic record
Abstract
In Australia, a means-tested old age public pension is paid from general tax revenues. A full pension (equivalent to about one quarter of the average wage) is currently paid to more than half the aged population and a reduced pension is paid to another one quarter of the aged population. About twenty per cent receive no old age public pension due to the level of their income or assets. There is also a compulsory system for the vast majority of employees requiring employers to contribute at least 7 per cent of salaries into a superannuation plan. (This minimum rate is rising gradually to reach 9 per cent in 2002.) More than 80 per cent of superannuation benefits are received as lump sums and when public sector employees are excluded, the figure rises to almost 90 per cent. The market for private life annuities with longevity insurance is very small. Greater use is made of allocated annuities, which are similar to income drawdowns in the United Kingdom or scheduled withdrawals in Latin American countries. The value of life annuities, measured by the Money's Worth Ratios, compares favorably with that of annuities available in the United States and the United Kingdom. But these are calculated on the basis of conservative government bond yields. Allocated annuities are perceived to have considerable advantages in terms of both flexibility and higher potential returns and are preferred by many investors despite the absence of longevity insurance. 1
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.088 | 0.024 |
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".