Bibliographic record
Abstract
Anti-terrorism law and policy is a rapidly evolving field, and since the chapters in this book were last revised, between September and November 2004, there have been numerous developments in the various jurisdictions and areas of law covered in this book. We could not, in the late stages of production, provide a comprehensive update of all of these developments, but some of them were sufficiently important and relevant to the chapters in this book as to warrant a brief mention in a postscript. United Kingdom: the House of Lords rules on indefinite detention of non-nationals On 16 December 2004, the House of Lords released its landmark decision in A . v. Secretary of State for the Home Department . The question in this case was whether the provisions in Part 4 of the Anti-terrorism, Crime and Security Act 2001 (ATCSA), which effectively permitted the indefinite detention of non-nationals of the United Kingdom who were suspected of being involved with international terrorism but who could not be deported, since they might be tortured in the receiving country, were inconsistent with the UK's obligations under the European Convention on Human Rights. The UK had formally derogated from Article 5(1)(f) of the Convention, which permitted the detention of foreign citizens only when ‘action is being taken with a view to 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.127 | 0.051 |
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".