Bibliographic record
Abstract
Curfews can be described as spatial and temporal borders that exclude and restrict mobility. During certain hours, the mere presence in a certain place, most often public spaces, is illegal, even if one has not done anything wrong. Curfews were imposed twice in Quebec since January 2021 (for a period of almost six months in total), allegedly to limit contacts and stop the COVID-19 virus transmission. But this spatiotemporal public health measure rapidly became a repression tool. A very large number of statements of offence, with associated fines and fees amounting to $1,550, were issued by the police for alleged curfew violations. In this chapter, we will draw both on quantitative data on the judicialization of the pandemic in Quebec and on qualitative data on the impact of the pandemic on homeless people to shed light on the socio-legal effects of the curfew, which seem to have been in the blind spot of Quebec authorities. If everyone was affected by the curfews, marginalized people, and especially homeless people, suffer disproportionately its consequences and its enforcement.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".