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Record W4379530939 · doi:10.5038/1944-0472.16.2.2072

Counterterrorism Law and Policy in the United Kingdom, Canada, and Australia: A Comparative Perspective

2023· article· en· W4379530939 on OpenAlexaboutno aff
Nadav Morag

Bibliographic record

VenueJournal of Strategic Security · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsnot available
Fundersnot available
KeywordsKingdomPolitical scienceScope (computer science)Context (archaeology)Divergence (linguistics)Corporate governanceLawPerspective (graphical)Law enforcementEconomicsGeographyManagement

Abstract

fetched live from OpenAlex

This article looks at the similarities and differences in British, Canadian, and Australian counterterrorism laws and policies. Canada and Australia are contrasted with the United Kingdom because their respective approaches to counterterrorism are based on the British approach, and yet have evolved to take into account differences in the nature and scope of the threat and the differing styles of governance in place in Canada and Australia. The article looks at each country in the context of: counterterrorism laws; detention and disruption practices; investigatory approaches; intelligence and law enforcement institutions; and the treatment of foreign fighters. The article then draws some conclusions regarding the evolution and divergence of counterterrorism law and policy in these countries and posits a question for future research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.107
Threshold uncertainty score0.779

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.010
Science and technology studies0.0090.008
Scholarly communication0.0090.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.143
GPT teacher head0.406
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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