Western European Pensions Privatisation: A Response to Jay Ginn
Bibliographic record
Abstract
Our recent paper on state-mandated private pension schemes in Western Europe has been criticised by Ginn because it did not look specifically at the impact of private provision on women. This was not our intent, but she raises important issues that are largely ignored in economics-driven pension privatisation policy discourses. She has addressed this omission by demonstrating that private pension provision may result in significant levels of economic disadvantage among women retirees. We do not disagree with the broad thrust of her analysis and its conclusions. However, because she has failed to appreciate the crucial difference between voluntary and state-mandated private pension provision, her thoughtful analysis does not invalidate our proposition that the state-mandated provision of private pensions in Western Europe is consistent, to varying degrees, with the notion of collective responsibility for needs satisfaction.
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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 | 0.028 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.032 | 0.023 |
| Insufficient payload (model declined to judge) | 0.004 | 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".