Ageing and the economic life cycle: The National Transfer Accounts approach
Bibliographic record
Abstract
OBJECTIVE: To illustrate the use of National Transfer Accounts (NTA) for understanding ageing and the economic life cycle in Australia. METHODS: The NTA methodology is applied utilising a range of unit record, demographic and administrative data sets from 1981 to 2010. RESULTS: During early and later life, total consumption (public and private) is greater than labour income. On a time series and cohort basis, we show that each successive generation has improved their level of well-being (as measured by consumption) relative to the previous years or previous cohorts from 1981 to 1982 onwards. We also show a substantial increase in labour income earned by mature age workers over this period. International comparisons show Australia to have consumption and labour income age profiles very similar to those of Canada but dissimilar to many other countries, driven by differences in demographic and policy settings. CONCLUSION: The NTA approach provides a powerful framework to track differences in the economic life cycle across age groups, across time, across cohorts and across countries.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".