Austerity as an opportunity for union revival: Québec public school teachers
Bibliographic record
Abstract
Abstract This article proposes an account of how two teachers’ labour federations have been reacting to austerity measures in public education. Current austerity measures have coincided with the renewal of collective agreements, thus allowing the study of how unions link bargaining stances to wider issues of service quality and accessibility. Union responses are the result of at least three influences: the institutional framework for public sector collective bargaining and worker representation, the previous orientation of members and their organisations towards social and work relations, and ongoing innovations for renewal and member engagement. We posit that union responses can contribute to renewal if they are guided by concerns to redefine union purpose, union organisation and building capacities. Under these conditions, unions are able to engage members and push forward an alternative agenda to that of the government. In doing so, they may be able to forge temporary alliances with outside stakeholders, namely parents. Analysis of union responses should consider the dialectic between union renewal effort and the opportunities and constraints of the institutional framework for public sector collective bargaining. The challenge for these two labour federations is in sustaining member engagement and activism beyond the current context of collective bargaining.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".