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Record W2760261077 · doi:10.7202/1034533ar

La restructuration économique et l’ancrage territorial de la crise de l’État-providence

2016· article· fr· W2760261077 on OpenAlexvenueno aff
Pierre Maclouf

Bibliographic record

VenueInternational Review of Community Development · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Le thème de la « crise de l’État-providence » est abordé ici sous l’angle du pouvoir local. Le niveau étant défini comme « le cadre concret où se nouent les relations entre production économique et appropriation, par les groupes bénéficiaires, des transferts sociaux ». Reprenant les résultats d’une recherche menée à l’Institut d’études politiques de Paris, l’auteur se penche sur trois milieux de vie différents situés dans le contexte français : un bassin d’emploi de vieille souche industrielle, Saint-Quentin, des cantons ruraux du Limousin et la commune d’Arles dans le sud-est de la France, qui repose sur une économie diversifiée. L’étude des relations entre l’État et les collectivités locales à partir de ces trois exemples permettent de bien voir qu’il existe en fait un ancrage territorial de l’État que les mises à jour des logiques générales ont souvent tendance à gommer. Il ressort au contraire que l’État-providence s’est construit en intégrant, dans l’élaboration de ses politiques sociales, les particularismes locaux. En conclusion l’auteur propose quelques perspectives en vue de surmonter la crise actuelle de l’État-providence. Il aborde alors un principe de « reterritorialisation » du social ouvert sur le développement et la participation populaire. Le défi est de ne pas se limiter à une « simple régulation de la crise ».

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0050.016
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.063
GPT teacher head0.354
Teacher spread0.291 · 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
Published2016
Admission routes1
Has abstractyes

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