Struggling Universities: Simon Fraser University and the Crisis of Canadian Public Education
Bibliographic record
Abstract
This article surveys the recent transformation of Simon Fraser University (SFU) against the backdrop of the crisis of Canadian public post-secondary education. The article contends that the Canadian model for the public funding of mass higher education that became consolidated in the postwar years is coming to an end, and that the metamorphosis of SFU over recent decades illuminates some of the tensions, tendencies and conflicts within what the Edu-factory Collective (2010) has called a double crisis: that of the university on the one hand, and of the global financial system on the other. Three processes in particular are at the heart of this transformation: a) the increasing importance of private capital, management and branding of the university in an era of decreased public funding; b) the university’s expansion across the urban fabric, in a process that brings displacement and gentrification; and c) the emergence of hybrid public-private models of educational delivery that cater to global markets for tuition dollars. Within this transformation, the article also points to lines of tension that are emerging out of these processes, creating conflicts and moments of encounter between the labour organizations, student groups and anti-gentrification activists struggling against the what Andrew Ross (2009) has called the global university.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.056 | 0.019 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 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".