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Protest Avoidance: Labor Mobilization and Social Policy Reform in France

2006· article· en· W2274017153 on OpenAlexaff
Daniel Béland, Patrik Marier

Bibliographic record

VenueMobilization An International Quarterly · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBlameMobilizationPoliticsScope (computer science)Political sciencePolitical economySocial movementPower (physics)PensionPublic administrationEconomicsSocial psychologyPsychologyLaw

Abstract

fetched live from OpenAlex

Students of public policy and social mobilization alike should pay more attention to the political strategies of protest avoidance. Distinct from traditional blame-avoidance strategies, protest avoidance occurs when elected officials, facing direct and nearly inescapable blame, attempt to reduce the scope of social mobilization triggered by unpopular reforms. In recent decades, successive French governments have introduced major, unpopular reforms in the field of public pensions, and because of the concentration of state power in France, avoidance of blame was nearly inescapable. Focusing on the 2003 pension reform, we argue that by dividing the labor movement through strategic bargaining, and by launching controversial reforms during or immediately before the summer holiday season, French governments reduced the scope of labor mobilization and facilitated the enactment of these proposals. Beyond the field of social policy, the concept of protest avoidance could shed new light on an understudied phenomenon: the strategies political actors pursue to reduce the scope of social mobilization against them.

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)0.006
metaresearch head score (Gemma)0.005
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 score0.052
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0080.011
Scholarly communication0.0070.002
Open science0.0010.004
Research integrity0.0040.002
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 head0.011
GPT teacher head0.327
Teacher spread0.315 · 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

Citations21
Published2006
Admission routes1
Has abstractyes

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