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Record W2099724380 · doi:10.1177/1748895809336377

The illicit firearms trade in North America

2009· article· en· W2099724380 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCriminology & Criminal Justice · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicGun Ownership and Violence Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsVariety (cybernetics)SpeculationPolitical scienceCriminologyGun violenceBusinessGun controlPoison controlSuicide preventionLawEnvironmental healthFinanceSociologyMedicine

Abstract

fetched live from OpenAlex

Gun violence in North American is the subject of much speculation and debate, often based on limited or incomplete empirical evidence. We summarize the regulatory frameworks in Mexico, the United States and Canada, and provide statistics on gun misuse in these countries. Based on our analysis of publicly available information on sources of crime guns, we conclude that while the United States is a major supplier of illegal handguns to Canada and illegal firearms of all types to Mexico, quantifying the extent of its role, particularly in Mexico, is difficult because of data limitations. Still more difficult is to project the consequences of an effective crackdown by US authorities. If the illicit supply from the USA dried up, the criminal gangs could turn to a variety of other sources that already appear to be playing some role. A complete analysis of these issues must await more complete disclosure by the authorities of data on gun sources and trafficking investigations.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.827

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.114
GPT teacher head0.381
Teacher spread0.267 · 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