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The Politics of Social Policy Language

2011· article· en· W1915785117 on OpenAlexafffund
Daniel Béland

Bibliographic record

VenueSocial Policy and Administration · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversity of Saskatchewan
FundersCanada Research Chairs
KeywordsSocial policyReflexivityPoliticsWelfare stateSociologyAction (physics)Meaning (existential)State (computer science)Social WelfarePolitical sciencePolitical economyEpistemologySocial sciencePositive economicsLaw and economicsLawEconomics

Abstract

fetched live from OpenAlex

Abstract A number of scholars have recently shown that key social policy concepts like ‘welfare state’ are both vague and problematic. Drawing on the international literature on the role of ideas in social policy, this article compares the development of two major policy concepts in two countries where the language of social policy is openly contentious: the USA and France. Focusing on the last three decades, the article discusses the meaning and development of the concepts of ‘social security’/‘sécurité sociale’ and ‘welfare state’/‘État‐providence’ in both countries. As suggested, these two concepts have long been controversial, in part because they are typically involved in the inherently political drawing and redrawing of the contested boundaries of state action. Overall, the article explains how the comparative analysis of social policy language can help scholars adopt a more reflexive approach.

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)0.028
metaresearch head score (Gemma)0.021
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0110.084
Scholarly communication0.0200.012
Open science0.0010.008
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0060.001

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 head0.052
GPT teacher head0.385
Teacher spread0.333 · 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

Citations23
Published2011
Admission routes2
Has abstractyes

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