Bibliographic record
Abstract
COMPARATIVE ANALYSIS The foregoing analyses of redistributive actions and reactions in Canada, Britain, Australia and the US describe and explain how each governing party devised transfer programmes. Of course, these accounts are historically incomplete; like other works in comparative politics my aim is not detailed description but analytic narrative (Bates et al. , 1998). Rather than registering events I focus on those critical junctures that set the preconditions or saw the main battles taking place. In this chapter I review the material presented from an explicitly comparative perspective in order to highlight similarities and differences among the four countries. On the basis of their historical experience, it is possible to outline a set of propositions about the incentives for income redistribution in a liberal democracy. The story of why we observe differences in inequality movements is necessarily incomplete because of the confluence of market, social, demographic, institutional and policy forces combined with behavioural changes by individuals, families and households. My account concentrated primarily on actor-centred institutionalism and showed that interdependent strategic action within party organisations sheds considerable light on redistributive games. The game theoretic models obviously did not determine the outcomes. What differed among the countries were the institutional settings within which those games were played. I analysed how party leaders of different ideological persuasions reacted to problems that arose from fundamental changes in international socio-economic conditions.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.162 | 0.035 |
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".