Aging and Inter-Generational Fairness: A Canadian Analysis
Bibliographic record
Abstract
Population aging in many countries has become a fundamental concern of public policy. One reason is fears that increasing numbers of elderly will place disproportionate burdens on their children in order to fund public pensions and health-related services. This analysis first discusses basic principles for assessing this question of intergenerational fairness. It then applies an empirically-based overlapping cohort dynamic microsimulation model for a quantitative analysis of the flows of taxes and cash and in-kind transfers for successive birth cohorts. The simulations cover both exogenous factors – specifically trends in life expectancy and the strength of the economy, and policy-related factors – specifically raising the age of entitlement to public pensions from age 65 to 70, and price versus relative wage indexing. The analysis concludes, among other points, that intergenerational differences are significantly smaller than intra-generational variations, and that the parents of the baby-boom generation are likely to benefit from the largest lifetime net transfers of any birth cohort from 1890 to 2010.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".