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Record W4387311782 · doi:10.32920/24236752.v1

City of hope, city of fear: Sanctuary and security in Toronto, Canada

2023· preprint· en· W4387311782 on OpenAlexaboutno aff
Graham Hudson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsJurisdictionContext (archaeology)PoliticsState (computer science)TemporalityPolitical scienceCorporate governancePublic administrationPolitical economySociologyGeographyLawBusiness

Abstract

fetched live from OpenAlex

<p>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.</p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.035
GPT teacher head0.331
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2023
Admission routes1
Has abstractyes

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