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Record W2982267739 · doi:10.1177/0019793919883815

Investigating the Dimensionality and Stability of Union Commitment Profiles over a 10-Year Period: A Latent Transition Analysis

2019· article· en· W2982267739 on OpenAlexaff
Alexandre J. S. Morin, Daniel G. Gallagher, John P. Meyer, David Litalien, Paul F. Clark

Bibliographic record

VenueIndustrial and Labor Relations Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsConcordia UniversityUniversité LavalWestern University
Fundersnot available
KeywordsConstruct (python library)Curse of dimensionalityConsistency (knowledge bases)Social psychologyPsychologyPeriod (music)Political scienceDemographic economicsEconomicsMathematicsStatisticsArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

The authors adopt a person-centered approach to the investigation of the dimensionality of the union commitment construct by capitalizing on a 10-year longitudinal study (from 1992 to 2002) of 637 union members in their first year of employment measured again 1 and 10 years later. Results reveal four distinct profiles of union commitment, presenting a stable structure over time. These profiles demonstrate consistency in commitment level across the three most common union commitment dimensions, thus questioning the necessity of adopting a multidimensional approach. Results show that union members became more similar to other members of their profiles over time, and that their union commitment became slightly less extreme as union tenure increased. Finally, results show that union commitment profiles predict union participation, in accordance with our expectations, and suggest that endorsing positive attitudes toward unions and their instrumentality was a stronger predictor of profile membership than was satisfaction with the actions of one’s own union.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.053
GPT teacher head0.306
Teacher spread0.253 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

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