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Record W7096042464

Federalism and Health Care Cost Containment in Comparative Perspective’, Publius: The

2009· article· en· W7096042464 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsFederalismRetrenchmentCooperative federalismVetoArgument (complex analysis)Welfare stateSocial policyWelfareSocial Welfare
DOInot available

Abstract

fetched live from OpenAlex

Despite widespread agreement over the connection between federalism and social expenditures during times of welfare state expansion, disagreement exists concerning federalism’s role in the retrenchment era. Existing approaches fail to recognize institutional variation among federal states. Analysis of Britain, Germany, and Canada suggests that federalism may promote or hinder health care retrenchment depending upon how it structures the relationship between regional and national governments. Power-sharing federalism hinders health care reform by increasing the institutional obstacles to unpopular cutbacks. Power-separating federalism facil-itates reform by creating opportunities for blame avoidance without substantially increasing the number of veto players. These findings challenge traditional linear or dichotomous models of federalism, suggesting the need for an approach that captures how particular types of federalism affect retrenchment politics. Comparative social policy literature generally relies on a shallow understanding of the role of federalism in welfare politics. Federalism is largely understood as one of a number of institutional ‘‘veto points’ ’ like bicameralism or presidentialism that serves as a brake on welfare state expansion. By fragmenting political authority and increasing the number of decision makers involved in policymaking, federalism expands the opportunities for opponents of the welfare state to block major legislation. Empirical evidence consistently confirms the role of federalism in constraining social expenditures and welfare state programs (Huber and Stephens

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.012
Scholarly communication0.0060.006
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.000

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.

Opus teacher head0.064
GPT teacher head0.408
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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