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Record W2798069249 · doi:10.3138/cjccj.2017-0052.r1

What's in a Name? Shifting Identities of Traditional Organized Crime in Canada in the Transnational Fight against the Calabrian ‘Ndrangheta

2018· article· en· W2798069249 on OpenAlexvenueaboutno aff
Anna Sergi

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsLaw enforcementOrganised crimeCriminologyClanNarrativeEthnic groupPolitical scienceEnforcementLawSociology

Abstract

fetched live from OpenAlex

The Italian antimafia authorities have warned Canadian law enforcement about the risks and the growing concerns for the infiltration of clans of the Calabrian mafia, known as ‘ndrangheta, in Eastern Canada. 3 The alarm linked to the rise of the ‘ndrangheta challenges the paradigms of traditional organized crime in Canada, because the ‘ndrangheta is presented as traditional but also innovative and more pervasive than other mafia-type groups. Through access to confidential investigations and interviews of key specialist law enforcement teams in Toronto and Montreal, this article investigates today's institutional perception of mafia – the ‘ndrangheta in particular – in Canada when compared to Italian conceptualizations. I will argue that the changes in narratives in Canada can be read in relation to changes in the Italian identity in the country, moving towards regionalization and specialist knowledge of ethnic differences.

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)0.002
metaresearch head score (Gemma)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.982

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0350.028
Scholarly communication0.0120.002
Open science0.0020.004
Research integrity0.0020.004
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 head0.085
GPT teacher head0.291
Teacher spread0.206 · 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

Citations12
Published2018
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénaleSame topicCrime, Illicit Activities, and GovernanceFrench-language works237,207