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Record W2190728522 · doi:10.54648/ijcl2010018

The Role of Women’s Groups in New Zealand, UK and Canadian Trade Unions in Addressing Intersectional Interests

2010· article· en· W2190728522 on OpenAlexaboutno aff
Julie Douglas, Jane Parker

Bibliographic record

VenueInternational Journal of Comparative Labour Law and Industrial Relations · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceGender studiesInternational tradeDemographic economicsSociologyBusinessEconomics

Abstract

fetched live from OpenAlex

Trade union women’s groups (WGs) may be defined as collective mechanisms such as women’s committees, conferences, networks, caucuses, branches/locals and training courses located within the wider union setting (cf. independent, self-organized WGs). The study draws on national surveys of trade unions in the UK, Canada, and New Zealand to examine the role(s) played by WGs, particularly in terms of voicing and advancing diverse or intersectional interests. Diversity builds on the more or less stable identities on which ‘difference’ ideas of (gender) equality are premised. Intersectionality is defined here as recognition of a person or group’s membership in more than one marginalized group, and intersectional interests as (i) interests held by subgroups of women (e.g., ethnic minority women); (ii) interests which transcend gender but may have gendered impacts; and (iii) more traditionally conceived gender interests which emphasize women’s situation relative to that of men (i.e., ‘intra-’, ‘trans-’ and ‘inter-gender’ interests). We also examine the equality approaches that underpin these pursuits before considering how intra-WG, union, and wider contexts help account for similarities and differences in union WG foci in the three countries. Based on extant research and the study’s empirical findings, the concluding discussion considers the broad directions in which UK, Canadian and New Zealand WGs may be headed in terms of representing intersectional interests and what this may mean for internal cohesion and union revitalization.

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)0.010
metaresearch head score (Gemma)0.014
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 score0.081
Threshold uncertainty score0.585

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.010
Science and technology studies0.0230.015
Scholarly communication0.0130.006
Open science0.0030.011
Research integrity0.0020.002
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 head0.036
GPT teacher head0.321
Teacher spread0.285 · 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

Citations5
Published2010
Admission routes1
Has abstractyes

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Same venueInternational Journal of Comparative Labour Law and Industrial RelationsSame topicLabor Movements and UnionsFrench-language works237,207