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Record W4300803112 · doi:10.46692/9781847426611.006

Welfare state institutions, unemployment and poverty: comparative analysis of unemployment benefits and labour market participation in 15 European Union countries

2011· other· en· W4300803112 on OpenAlexaboutno aff
M. Azhar Hussain, Olli Kangas, Jon Kvist

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsnot available
Fundersnot available
KeywordsUnemploymentWelfare statePovertyEuropean unionEconomicsWelfareLabour economicsState (computer science)Eu countriesInternational economicsEconomic growthPolitical scienceMarket economy

Abstract

fetched live from OpenAlex

Introduction Much intellectual effort has been expended on debating welfare state regimes – whether they exist (and, if so, how many), what their central characteristics are and whether they are becoming more similar or not. In his Three worlds of welfare capitalism , which launched an avalanche of welfare regime studies, Gøsta Esping- Andersen (1990) emphasised that a welfare state regime consists of a multifaceted interplay between labour markets and social policies. From this perspective he distinguished three clusters of welfare state: Nordic, Liberal and Corporatist regimes. The hallmark of the Nordic welfare state, consisting of Denmark, Finland, Norway and Sweden, is a high level of employment, with high income protection when one is unemployed, sick, disabled, elderly, etc. As a consequence of these interacting factors, poverty rates in all population categories – the employed, the unemployed, the retired, etc – are low. In the Liberal welfare state means-tested or low flat-rate benefits dominate and, as a consequence of the low level of social protection, poverty among the welfare recipients is common. Typical examples of this welfare state model are: Australia, Canada, Ireland, New Zealand, the UK and the US. The third cluster, the Corporatist – typical of the Central European countries Austria, France, Germany, Belgium and the Netherlands – combines high social insurance benefits for the labour market insiders and a strong degree of familialism that supports traditional gender roles. To preserve class and status difference, social security is organised according to occupational lines. Esping-Andersen's triad has been expanded to include a fourth model, the Southern European welfare state (Greece, Italy, Portugal and Spain), characterised by generous entitlements for the core workers – the replacement rates are among the highest in the EU hemisphere – while other forms of social protection are underdeveloped and the extended family plays a central role in care-giving. Female labour force participation is thus very low in comparison to the other regimes (Ferrera, 2010). This chapter examines the interaction between the labour market, employment and social security in different welfare state regimes. More specifically, we investigate to what extent, if any, we can find regime-based differences in labour markets, in the generosity of unemployment insurance or in the economic consequences of being employed, becoming unemployed for a shorter or longer period and becoming employed again. Our study spans the mid-1990s to the late 2000s.

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)0.003
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.268
Teacher spread0.221 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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