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Record W2701172916 · doi:10.1177/0958928717700563

Federalism, policy change, and social security in Belgium: Explaining the decentralization of family allowances in the Sixth State Reform

2017· article· en· W2701172916 on OpenAlexafffund
Daniel Béland, André Lecours

Bibliographic record

VenueJournal of European Social Policy · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversity of OttawaUniversity of Saskatchewan
FundersCanada Research Chairs
KeywordsDecentralizationVetoFederalismPoliticsSocial securityPolitical scienceState (computer science)FrenchClientelismPublic administrationGovernment (linguistics)Political economySociologyDemocracyLawHumanities

Abstract

fetched live from OpenAlex

The debate on social policy change is not only about the evolving nature of social benefits but also about change in their territorial organization. This territorial issue is central in Belgium. In 2011, the Sixth State Reform featured the decentralization of family allowances, a component of social security. This article explains why such decentralization occurred in Belgium despite the fact that Francophone parties, which effectively have veto power over constitutional reform, had long insisted that no portion of social security would ever be transferred to the constituent units. We argue that increasing political pressure generated by the surge of the Nieuw-Vlaamse Alliantie (N-VA) in the context of the government formation crises altered how Francophone parties assessed both the national unity situation and their own political interests. The article also discusses the policy and political implications of the decentralization of family allowances in Belgium.

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)0.004
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: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.008
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.113
GPT teacher head0.393
Teacher spread0.280 · 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

Citations45
Published2017
Admission routes2
Has abstractyes

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