Immigration, Sanctuary Policies, and Public Safety
Bibliographic record
Abstract
US Immigration and Customs Enforcement (ICE) detainers—the requests from ICE to a state or local law enforcement agency to hold someone until the person can be taken into immigration custody—have been instrumental in supporting the growing number of deportations from the United States. However, as migrant detentions expanded after 9/11, law enforcement agencies have been increasingly reluctant to comply with ICE's detainers, due to the cost incurred by detention centers when holding immigrants for an extended period and the possible violation of migrants’ civil rights. Such reluctance has earned these law enforcement agencies the label of “sanctuary cities.” ICE has denounced this behavior, arguing that it interferes with the agency's ability to obtain custody of convicted criminals and makes communities less safe. Using data on detainers at the local law enforcement-agency level, we assess ICE's claims. We find that sanctuary policies do not hinder ICE's ability to obtain custody of convicted criminals and question the argument that such policies might make communities less safe. These findings are relevant for migration scholars and policymakers interested in gaining a better understanding of the public-safety implications of sanctuary policies aimed at immigrants in various receiving nations, including Canada, the UK, and the United States.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".