Immigration detention and the problem of time: lessons from solitary confinement
Bibliographic record
Abstract
In 2016, the Canadian Government launched an initiative to reform immigration detention, with the goal of creating a just and humane detention regime. In this paper, we argue that to achieve its stated goals, this initiative must address a core problem in the law of detention: the problem of time. This problem flows, in part, from there being no clear time limits on detention, and in part, from there being no clear standards for achieving release from detention. For insights into this problem, we turn to recent developments in the law of solitary confinement, which is similarly beset by the problem of time. Learning from solitary confinement, we argue that clear statutory time limits and meaningful independent oversight are necessary to ensure the just and humane regulation of detention. In their absence, the government's reforms may amount to window-dressing: detention will continue to be vulnerable to misapplication and misuse, and to destroy and dehumanise those in its care.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".