Pre-Trial Detention and Control Orders Under British Anti-Terror Legislation Post 9/11: Balancing a Need for Security with the European Convention on Human Rights – An Overview
Bibliographic record
Abstract
Contemporary British anti-terror legislation has been characterised by an extensive use of extra-ordinary detention measures: the Terrorism Act 2000 and Terrorism Act 2006 contain provisions, which enable the extended pre-charge detention of terror suspects beyond the limits of normal criminal procedure. The now repealed provisions of Part IV of the Anti-terrorism, Crime and Security Act 2001 allowed the indefinite detention of foreign national terror suspects on a quasi-judicial basis. Its successor, the Prevention of Terrorism Act 2005, enables the use of Control Orders, effectively a form of house arrest characterised by restrictions on an individual’s liberty. In short, these measures have in common the extensive limitation of the individual’s right to liberty under Article 5 of the European Convention on Human Rights. Whilst the judiciary have curtailed the most abhorrent manifestations of such extraordinary measures, as detailed, the legal framework as it exists today, still raises ECHR compliancy issues. Legal reformation should be sought to end such an impasse by amending at the very least the statutory framework already in place. Ideally anti-terror detention provisions should be brought back within the sphere of criminal law and in compliance with the ECHR.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".