(No) Access T.O.: A Pilot Study on Sanctuary City Policy in Toronto, Canada
Bibliographic record
Abstract
Introduction: The “sanctuary city” movement is a grassroots, human rights-based response to increased numbers of non-status migrants living and working in global cities (Faraday 2012; Sawchuk & Kempf 2008; Bhuyan 2012; OCASI 2012). Nonstatus migrants live in situations of extreme precariousness — they are subject to detention and deportation if identified by federal authorities; often work in poor conditions; are socially isolated; face poverty, abuse, and exploitation; and are unable to safely access essential social services, including those related to healthcare, education, labour, shelters, food banks, and police services (Gibney 2000; De Giorgi 2010; Noll 2010). In February 2013, Toronto became the first “sanctuary city” in Canada, which is currently styled “Access T.O.” Hamilton and Vancouver followed suit in 2014 and 2016, respectively. The primary objective of Access T.O. is to ensure that all residents are able to access municipal and police services, regardless of immigration status. The policy directs city officials not to: 1) inquire into immigration status when providing select services, 2) deny non-status residents access to services to which they are entitled, and 3) share personal or identifying information with federal authorities, unless required to do so by federal or provincial law (City of Toronto 2013).
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".