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Record W3010706896 · doi:10.1111/capa.12359

Made in Canada: The evolution of Canadian counter‐terrorism policy in the post‐9/11 world

2020· article· en· W3010706896 on OpenAlexaboutno aff
Stephanie Carvin, Nicole Tishler

Bibliographic record

VenueCanadian Public Administration · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsnot available
Fundersnot available
KeywordsTerrorismPolitical scienceCounter terrorismGovernment (linguistics)National securityAgency (philosophy)State (computer science)Foreign policyPublic administrationPolitical economySecurity policyProcess tracingLawSociologyPoliticsComputer securitySocial science

Abstract

fetched live from OpenAlex

Abstract Literature on Canada‐United States (US) counter‐terrorism (CT) cooperation from the early 2000s presumed that Canadian CT policy was driven by US security imperatives and fear, leaving little room for Canada to develop its own path in fighting terrorism. It presumed that: the Canadian government was more worried about the US reaction to terrorism than terrorism itself; Canadian security policy sought to be “separate but cooperative”; and Canadian policy was informed by “wise” understandings of the US. We argue these assumptions no longer hold. Since 2011, with the rise of the Islamic State and foreign fighter activity, the Canadian government took independent steps to address national security concerns in a multilateral environment. We use process tracing to track evolutions in the Passenger Protect Program (Canada's “no‐fly list” policy), showing how Canada has increasingly asserted agency in response to violent extremism. It suggests the prior scholarly consensus on the US role in Canadian CT policy must be rethought.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.558
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.271
Teacher spread0.240 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2020
Admission routes1
Has abstractyes

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