Limitations to Inclusive Unions from the Perspectives of White and Aboriginal Women Forest Workers in the Northern Prairies
Bibliographic record
Abstract
Several authors have argued that broadening the traditional understandings of union solidarity is necessary for union renewal. Concerns specific to workers from marginalized groups have been shown to challenge traditional understandings of union collectivity. This paper draws on interviews with white and Aboriginal women forest processing workers to argue that interrogating marginalized workers' negative representations of their unions can provide insights that will help to broaden traditional understandings of union solidarity. I use thematic analysis followed by critical discourse analysis to examine women workers' negative talk about unions. I present examples of how women's negative representations of their unions can be understood as different forms of collectivism when examined in the context of their lived experiences of work and unionism. Some white and Aboriginal women's representations of their unions wove individualistic anti-union statements together with their previous experiences of work highlighting the inequality between unionized and non-unionized workers in the community. The talk of other Aboriginal women critiqued the union for not representing them while demonstrating a sense of collectivity with other Aboriginal workers. By exploring linkages between women's negative representations of unions and their work experiences, unions can better understand the negative union sentiment of marginalized workers and use this to create more inclusive forms of solidarity.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.024 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".