Bibliographic record
Abstract
Abstract Contemporary sanctuary movements are organized, collective efforts to provide physical protection to migrants facing arrest and deportation by state authorities in receiving countries. Medieval sanctuary practiced by the Christian church was a permanent element of a legal system and protection was extended to felons, fleeing serfs, and debtors (Morgenstern 2009). Such provisions were later appropriated by the modern state in Europe and were essential to the development of early modern criminal law (Shoemaker 2010). Only in the late 1970s did sanctuary movements and their practices develop a strong connection to protecting asylum‐seekers from arrest and deportation in receiving countries rather than other kinds of fugitives. The defining practices of these movements first became manifest in the UK (see Weller 1987: 10). But it was during 1982 and 1983, and then sporadically during the next three decades, that sanctuary practices ostensibly stemming from Christian churches emerged fully in the US, Canada, and Western Europe, including Germany, France, the Netherlands, Switzerland, Norway, and Finland (see Lippert 2006: 4). These practices arose amid a dramatic increase in the number of asylum‐seekers in the West, and a corresponding escalation of national and international efforts to discourage and control their arrival, including the use of physical arrest and deportation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".