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Record W2042675483 · doi:10.1177/0950017003017002002

Mobilization and Change in a Trade Union Setting: Environment, Structures and Action

2003· article· en· W2042675483 on OpenAlexaff
Janice Foley

Bibliographic record

VenueWork Employment and Society · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsMobilizationCollective actionAffect (linguistics)Action (physics)Social movementTrade unionOrganizational structurePolitical sciencePublic relationsIndustrial actionSocial psychologyPsychologyEconomicsLabour economicsLawCommunication

Abstract

fetched live from OpenAlex

This case study, based on data collected from archival and interview sources, describes the variable efficacy over a 24-year period of a union-based women's committee. A theoretical model was developed that identified environmental factors, union and committee structures, and committee characteristics as variables that might affect the committee's effectiveness. Outcomes of three types were considered: structural changes that would benefit women, increased female participation in union decision making, and improved clauses in the collective agreement especially relevant to women. The study shows that while environmental factors and formal structures play an important role in achieving mobilization and change, the actions of the Social Movement Organization (SMO) itself, and of all the parties potentially affected by the SMO, are equally critical. The social movement literature complements the industrial relations and feminist organizational literatures in explaining the processes involved in successful collective action.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0090.009
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0020.001
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 head0.033
GPT teacher head0.292
Teacher spread0.259 · 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 designQualitative
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

Citations14
Published2003
Admission routes1
Has abstractyes

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