The Liberty of Non-Citizens : Indefinite Detention in Commonwealth Countries
Bibliographic record
Abstract
The book addresses the legality of indefinite detention in countries including Australia, the United Kingdom and Canada, enabling a rich cross-fertilisation of experiences and discourses. The issue has arisen where a government is frustrated in its ability to remove a non-citizen subject to a removal order and employs a power to detain him until removal. The cases raise fundamental questions about the nature and extent of immigration powers, the legal position of non-citizens and counter-terrorism law and policy. More broadly, the judgments have become key reference points in discussions of constitutionalism, rights and a range of contemporary issues in public law. The book analyses the legal context, reasoning and implications of the case law on indefinite detention. It argues that the law of each jurisdiction contains ample resources to support a ruling that indefinite detention is illegal. It demonstrates that, taking into account variations in legal frameworks and doctrines, a judge’s response to indefinite detention is determined by his or her answer to the question whether a non-citizen, subject to a removal order, retains a right to liberty. It details how a judge’s answer flows through his or her adjudication on the scope of the relevant exception to liberty. The thesis on which the book is based won the 2010 Marks Medal from the University of Toronto Law Faculty for the best graduate thesis.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| 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 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".