The University as a Neoliberal and Colonizing Institute: A Spatial Case Study Analysis of the Invisible Fence between York University and the Jane and Finch Neighbourhood in the City of Toronto
Bibliographic record
Abstract
Jane and Finch is notoriously known in the City of Toronto as a high profile “Priority Neighbourhood” characterized by poverty, crime and violence. And yet, it is situated in close proximity to York University, a place of higher learning characterized by modernism, order, multiculturalism, and innovation. Using a spatial analysis, the first half of this essay traces the social, cultural, and historical development of Jane and Finch and York University, contrasting the rapid development and expansion of York University in relation to the slow growth and deteriorating living conditions of Jane and Finch. The second half of the essay explores the racialization of physical and social differences between York University and Jane and Finch. In particular, I explore how interlocking systems of domination produce, maintain, and (re)produce an invisible fence that constitutes York University as a civilized space and Jane and Finch as a spectacle of violence and delinquency. Overall, this article uses York University as a case study to argue that the university, as an extension of the State, participates in a neoliberal and colonizing project that constructs York University as a safe place of higher learning at the expense of social marginalization, stigmatization, and exclusion of the Jane and Finch community and Othering of its residents. By the racialization of Jane and Finch and Othering of its immigrants and visible minorities, York University exemplifies the processes by which whiteness is protected and privileged and the university’s perpetuation of poverty and violence in Jane and Finch are masked.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.032 | 0.024 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".