Rebellious Responses to the Walmartization of Canadian Higher Education | 125 Rebellious Responses to the Walmartization of Canadian Higher Education
Bibliographic record
Abstract
ABSTRACT: Canadian higher education has been heading in a general neoliberal direction for quite sometime with most universities employing similar strategies. The example of Wilfrid Laurier Univeraity is used to first illustrate some of those strategies and then later on to show a relatively new one. WLU’s Integrated Planning and Resource Management (IPRM) process is very much like similar processes being undertaken at a number of Canadian Universities. It is a management strategy to more easily enable unpopular cuts to staff and programs and legitimate the process through enlisting faculty “cooperation”. The APRM is the faculty union’s commissioned alternative report and will be a focal point of resistance with its very different set of recommendations. However, an argument is also made that, though while worthwhile, such-like actions will not nearly be enough to prompt a significant change in institutional direction. It is argued that though there are many prongs to the neo-liberal attack upon higher education, the most significant one is the casualization of its teaching labour force. It is argued that strong action by tenured and tenure track faculty is required to not only eradicate the injustices inherent in the situations of our contract academic colleagues but that this is actually the key to preserving quality education.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.068 | 0.029 |
| Scholarly communication | 0.016 | 0.003 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.013 | 0.022 |
| Insufficient payload (model declined to judge) | 0.011 | 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".