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Record W2524487107 · doi:10.15173/glj.v7i3.2536

The Characteristics of UK Unions' Environmental Activism and the Agenda's Utility as a Vehicle for Union Renewal

2016· article· en· W2524487107 on OpenAlexvenueno aff
Thomas Farnhill

Bibliographic record

VenueGlobal Labour Journal · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationIndustrial relationsPolitical scienceProduct (mathematics)Public administrationPolitical economyEconomicsLaw

Abstract

fetched live from OpenAlex

<p><em>A survey of 22 UK unions’ environmental activism suggests that it is generally unrelated to either membership trends or unions’ financial health, although large, multi-sector unions are generally the most active. Adequate resourcing, discussion of environmental matters at senior levels of the union and positive relations with external environmental organisations are all associated with environmental activism. Although the agenda appears popular with members and encounters little resistance from employers few unions currently evidence serious or regular engagement and it is largely confined to large and/or public sector workplaces where the union is already well-established. Limited adoption may be attributable to a combination of the absence of supportive legislation and public funding, the agenda’s inability to generate an attractive ‘product’ for members, and already crowded local agendas. However, most unions anticipate their environmental agenda expanding in the future. </em></p><p><strong>Key Words</strong>: unions; environment; labour-environment relationship; employee relations; union renewal</p>

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)0.022
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.003
Scholarly communication0.0060.002
Open science0.0010.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.010
GPT teacher head0.271
Teacher spread0.260 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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