The Role of Women’s Groups in New Zealand, UK and Canadian Trade Unions in Addressing Intersectional Interests
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.023 | 0.015 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".