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Record W2808851125 · doi:10.1177/1024258918781732

Flexicurity and the dynamics of the welfare state adjustments

2018· article· en· W2808851125 on OpenAlexaff
Oldřich Bubák

Bibliographic record

VenueTransfer European Review of Labour and Research · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsFlexicurityAusterityWelfare statePoliticsEconomicsState (computer science)Financial crisisOrder (exchange)Economic systemWelfarePolitical sciencePolitical economyMarket economyMacroeconomics

Abstract

fetched live from OpenAlex

The disruptions of the recent global financial crisis intensified a number of industrial and economic challenges and brought forward a set of often contradictory solutions. Here, we focus on two alternative views on how to (re)establish economic competitiveness and enable growth – flexicurity and austerity. There is much to be learned about the future of these conflicting recipes across changing political economies, particularly considering the importance of the social partners in the development of flexicurity, and their differential ability to influence welfare state outcomes more broadly. Two questions emerge. Attentive to the role and capacity of the social partners, what can we learn about the dynamics of the ongoing welfare state adjustments? How do we make sense of labour market politics in this paradoxical environment? In order to help answer these, we visit the United Kingdom and Denmark – one state offering modest social and employment security, the other a paragon of flexicurity – and find their divergent philosophies, institutional development, and organisational interactions explain not only their respective choices in the aftermath of the crisis, but also their prospects for socially oriented labour policies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.828
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.404
Teacher spread0.351 · 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 teacher head, not a consensus.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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