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Record W4388991454 · doi:10.1111/spol.12986

Welfare state regimes and social policy resistance to fiscal consolidations

2023· article· en· W4388991454 on OpenAlexafffund
Olivier Jacques

Bibliographic record

VenueSocial Policy and Administration · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversité de Montréal
FundersFonds de Recherche du Québec-Société et Culture
KeywordsRetrenchmentWelfare stateSocial insuranceEconomicsWelfareSocial WelfarePoliticsMarket economyResistance (ecology)Social policyEconomic policyPolitical science

Abstract

fetched live from OpenAlex

Abstract We study how welfare states regimes influence the effect of episodes of fiscal consolidations on the four main components of the welfare state: social investment, pensions, healthcare and labour market insurance. Welfare state regimes are associated with distinct social policy legacies that feedback into political competition by shaping the size and influence of different coalitions of constituents. Using data from 1980 to 2014 in 16 OECD countries, we find that labour market insurance is more vulnerable to consolidations in Liberal regimes, while social investments are more resistant to consolidations in Nordic regimes. In the Continental regime, which overlaps with Social Health Insurance systems, healthcare is more resistant to consolidations. Finally, pensions are more resistant to consolidations in the Southern regime. These findings contribute to the study of the comparative political economy of welfare state retrenchment.

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)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.042
GPT teacher head0.386
Teacher spread0.343 · 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 designTheoretical or conceptual
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

Citations5
Published2023
Admission routes2
Has abstractyes

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