MétaCan
Menu
Back to cohort
Record W3132071353 · doi:10.1177/1473779521991557

Violent crime, hate speech or terrorism? How Canada views and prosecutes far-right extremism (2001–2019)

2021· article· en· W3132071353 on OpenAlexaffabout
Michael Nesbitt

Bibliographic record

VenueCommon Law World Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTerrorismFar rightIdeologyLawPolitical scienceCriminologyRhetoricCriminal lawSociologyPolitics

Abstract

fetched live from OpenAlex

Fifty-six individuals were charged with terrorism between December 2001 when Canada first enacted its antiterrorism criminal offences and December 2019. Not a single such individual was associated with a far-right group or espoused a far-right ideology. Over the same period of time, Canada saw a rise in far-right violence and crime, including several deadly attacks that raised the spectre of terrorism. This article seeks to identify why terrorism has not been associated with the activities of those on the far right, how Canada has prosecuted far-right violence if not for terrorism and what the implications are for Canada’s criminal prosecutions going forward. It finds that since December 2001 all publicly reported hate speech cases and cases where an individual’s sentence was aggravated for hate have involved individuals espousing far-right rhetoric; likewise, all but one case where the media raised the spectre of terrorism but no such charge ensued can be described as being motivated by far-right ideation. In the result, Canadian law punishes more seriously Al-Qaida (AQ)-inspired extremism than far-right extremism, while stigmatizing the former more than the latter. The time has thus come to tackle head-on the concept of ideology in Canadian criminal law, and how the law treats various ideologies.

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)0.005
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.095
Threshold uncertainty score0.687

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0060.005
Scholarly communication0.0070.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.334
Teacher spread0.286 · 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 designQualitative
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

Citations10
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueCommon Law World ReviewSame topicTerrorism, Counterterrorism, and Political ViolenceFrench-language works237,207