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Record W1537943999 · doi:10.1108/01437720210428397

Rethinking the union membership/job satisfaction relationship

2002· article· en· W1537943999 on OpenAlexaffabout
Stéphane Renaud

Bibliographic record

VenueInternational Journal of Manpower · 2002
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsJob satisfactionOrdered probitPsychologyDemographic economicsControl (management)Sample (material)Social psychologyProbit modelDifferential (mechanical device)EconomicsEconometricsManagement

Abstract

fetched live from OpenAlex

This paper examines differences in the level of job satisfaction reported by union workers and non‐union employees. There is a strong belief in the literature that union status reduces job satisfaction. Based on different national probability samples, previous studies have generally failed to adequately control for differences in working conditions between the two sectors while studying the impacts of unions on job satisfaction. Union workers generally have a poorer working environment. The negative relationship reported between union status and job satisfaction might only reflect this differential if differences in working conditions are not taken into account. Using a large representative sample of 3,352 workers from the Canadian General Social Survey of 1989, this study replicates previous econometric specifications. The results of ordered‐probit regression show a negative relationship between union status and job satisfaction, but as expected, this relationship disappears when an adequate control for differences in working conditions is applied. It is concluded that union status is not negatively associated with job satisfaction in Canada.

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)0.005
metaresearch head score (Gemma)0.019
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.433

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.132
GPT teacher head0.407
Teacher spread0.275 · 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

Citations87
Published2002
Admission routes2
Has abstractyes

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