Bibliographic record
Abstract
The sanctuary city movement is a transnational human rights-based response to non-status migrants living and working in global cities. In many ways it is an oppositional mode of politics that challenges the exclusive authority of central governments over migration and political membership. Borrowing from critical legal geography, academics speak of the city as a ‘scale’ of urban belonging that can supersede national or international scales. However, clusters of practices, networks, and rationalities of governance are not necessarily confined to one scale. Urban securitisation is an apt example, where national governments cast off constraints of ‘high law’, shifting mechanisms of border control to regional and local scales. Research in Canada, the United States, and elsewhere demonstrates that local police, state authorities and, indeed, non-state actors, participate in the management of the (perceived) risks that non-status migrants pose to state and citizen. In this context, this chapter examines the uneasy relationship between sanctuary and security in Toronto, Canada. It does so by reflecting on the utility of the concepts of jurisdiction and temporality in better understanding how the securitisation of irregular migration has taken hold in the city. Placing this process in historical and jurisdictional context, it explores possible antidotes to urban securitisation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.023 | 0.006 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".