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Record W4233343559 · doi:10.1017/cbo9780511493874.023

Canada's response to terrorism

2005· book-chapter· en· W4233343559 on OpenAlexaffabout
Kent Roach

Bibliographic record

VenueCambridge University Press eBooks · 2005
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTerrorismScrutinyPolitical scienceWorld trade centerImmigrationGovernment (linguistics)Patriot ActSafe havenLawNational securityHomeland securityPublic administration

Abstract

fetched live from OpenAlex

Canada's response to terrorism has been dramatically affected by 9/11. Canadians died in the horrific attacks on the World Trade Center, but so did the citizens of many other countries. What was unique about Canada's response to 9/11 was the border it shares with the United States. The border meant that Canada felt the repercussions of the swift American response to the attacks in an immediate and profound manner. For example, when the United States closed its air space that terrible day, it was Canada that accepted over 200 airplanes destined for the United States, including one plane that was erroneously believed to have been hijacked. Canada also was affected by erroneous claims that some of the terrorists had entered the United States through Canada, as indeed had occurred before and may likely occur again given the millions who cross the border each day. Canada was also singled out in the USA Patriot Act which contained a whole section entitled 'Defending the Northern Border' providing for increased border guards and scrutiny of those entering the United States. Important components of Canada's anti-terrorism and immigration policies have been established in border agreements with the United States. Canada has drafted broad new anti-terrorism laws and developed a new public safety department of government with an eye to American perceptions that Canada might provide a safe haven for terrorists.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.471
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.217
Teacher spread0.199 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations12
Published2005
Admission routes2
Has abstractyes

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