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Record W2724278769 · doi:10.1111/bjir.12248

In Unions We Trust! Analysing Confidence in Unions across Europe

2017· article· en· W2724278769 on OpenAlexaff
Lorenzo Frangi, Sebastian Koos, Sinisa Hadziabdic

Bibliographic record

VenueBritish Journal of Industrial Relations · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsNarrativeRepresentation (politics)Industrial relationsPolitical scienceOrder (exchange)Demographic economicsEconomicsSociologyPolitical economySocial psychologyPsychologyPoliticsLaw

Abstract

fetched live from OpenAlex

Abstract Public institutions and trade unions in particular are often portrayed as facing a deep crisis. In order to better understand to what extent unions are still perceived as legitimate institutions from the society as a whole (working and non‐working individuals), we analyse the determinants of confidence in unions across 14 European countries between 1981 and 2009. Confidence in unions is explained through individual‐level variables (by a rational and an ideational mechanism) and contextual‐level factors (relevant economic and employment relations characteristics). Using data from the European Values Study (EVS) merged with contextual datasets, we develop a series of regression models to examine the main determinants of confidence in unions. We demonstrate that confidence in unions cannot only be traced back to the support from members and left‐wing oriented individuals but it is also related to non‐working individuals and vulnerable social groups, in particular when confronted with economic shocks. Our findings challenge both the ‘crisis of confidence’ in institutions and the ‘crisis of unionism’ narratives. Implications for union representation and organizing strategies are discussed.

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)0.002
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.111
GPT teacher head0.405
Teacher spread0.294 · 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 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

Citations42
Published2017
Admission routes1
Has abstractyes

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