Excursus: Ambivalences of a Sanctuary City. Rethinking borders: insights into the struggles of Toronto’s ‘Sanctuary City’ policy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Based on the North American model, Sarah Schilliger examines the successes and challenges that come with official ‘Sanctuary City’ status. With half of its 3 million inhabitants born outside of Canada, Toronto became the first Canadian city to commit to a Sanctuary City policy in 2013, and serves as the blueprint for the German Solidarity City network. Toronto’s Sanctuary City status was the result of a 10-year struggle fought by a broad alliance of civil society organisations. Under the umbrella of the ‘Access without Fear’ campaign, these organisations fought to stop deportations and to achieve residence security and fearless access to legal and social services for people with precarious legal status. Sarah Schilliger shows that a Sanctuary City also requires sufficient budget funds, public awareness campaigns and further education measures for officials and employees of public institutions if the security and protection of precarious status migrants are to remain more than just an empty promise.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it