Bibliographic record
Abstract
This report presents an empirical typology of pension regimes in the \nEuropean Union, the US, Canada, Australia and Norway. The categorisation is \nbased on 34 quantitative and qualitative characteristics of the mandatory parts \nof the pension systems in these countries. The empirical analysis shows that \nEsping-Andersen's classical distinction between liberal, corporatist and \nsocial-democratic welfare regime types does not entirely hold in the case of \npension systems. \nThe empirical traits of the various pension systems can be summarised on two \nmain dimensions: the general level of pension provision and the existence of \nprivate schemes within the mandatory part of the pension system. \nOn these dimensions four clusters of countries, or pension regime types, have \nbeen identified empirically. Two of those are as one would theoretically \nexpect: the corporatist group has rather high earnings-related pension \nbenefits, while the liberal pension regime type provides a more basic, \nmeans-tested pension. However, two other clusters are not in line with the \nstandard \nclassification of welfare regimes. In the 'moderate pensions' cluster, the \nlevel of pension provision is lower than in the corporatist countries, but it \nsurpasses the standards attained by countries with a liberal pension regime. In \ncountries belonging to the 'mandatory private' cluster, the government obliges \nemployees to participate in private pension schemes, which are \ngenerally funded and based on defined contributions. The pension level in this \ngroup is moderate or high. \n \nENEPRI \n This is not a publication of the Institute of Social Research of the \nNetherlands - SCP, but is published by European Network of Economic Policy Research Institutes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".