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Record W4324028665 · doi:10.32920/22266010.v1

Montreal’s Sanctuary Policy for Non-Status Migrants: Opportunity and Obstacles

2023· preprint· en· W4324028665 on OpenAlexafffundabout
Idil Atak, Graham Hudson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsUrban policyPublic administrationPower (physics)Political scienceSociologyEconomic growthUrban planningEconomicsEngineering

Abstract

fetched live from OpenAlex

In February 2017, the city of Montreal adopted a policy entitled Access to Municipal Services Without Fear with a view to allowing non-status migrants to access some municipal programs and services without fear of being arrested and removed from Canada. This article offers a critical analysis of the city of Montreal’s policy. We discuss the main barriers to implementation, namely, the limited jurisdictional power and authority of the city in migration matters and the municipal police’s refusal to comply with the policy. We draw on the conceptual framework of the sanctuary city to argue that the municipality crafted creative solutions to barriers as part of its bid to make the city more inclusive.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.111
Threshold uncertainty score0.803

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0280.012
Scholarly communication0.0100.002
Open science0.0030.005
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0080.000

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 head0.319
GPT teacher head0.534
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2023
Admission routes3
Has abstractyes

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