Learning on the picket line: investigating a politico-administrative regime
Bibliographic record
Abstract
In September 2011, approximately 1700 unionized non-academic staff at McGill University in Montreal, Quebec went on strike. Using institutional/political activist ethnography, this study examines the informal learning of non-academic staff during the strike and assesses how their experiences are coordinated through social relations. The data used in this study consists of non-structured interviews with union workers and organizers, along with the critical analysis of institutional texts. The study looks at the informal and non-formal learning of workers on strike and considers how participation in the strike promoted workers' understanding and knowledge of how the university is socially organized, and helped many of them gain a critical consciousness. In an era of increased corporatization of the higher education sector, this study documents the relationship between learning and action in the context of a significant, contemporary labour dispute at a major Canadian university. Further, grounded in an analysis of workers' experiences of the strike, it provides a potential resource for further inquiry into future labour and union struggles in universities in North America.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.042 | 0.035 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".