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Record W2260264931

Evaluating Canada's 1995 firearm legislation

2005· article· en· W2260264931 on OpenAlexaboutno aff
Gary A. Mauser

Bibliographic record

VenueJournal on firearms and public policy/Journal on firearms & public policy · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicGun Ownership and Violence Research
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationHomicidePoison controlOccupational safety and healthSuicide preventionInjury preventionHuman factors and ergonomicsGun controlComputer securityMedical emergencyBusinessEngineeringCriminologyForensic engineeringEnvironmental healthMedicinePolitical scienceLawPsychologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

In 1995 Canada amended its firearms law to require owner licenses and to create a universal firearm registry. Despite costing at least C$ 1 billion so far, the firearms program has failed to win the trust of the public or the police. This article examines the organizational problems of the firearms program and evaluates its effectiveness in improving public safety. Years after its inception, with virtually unlimited budgets, the firearms registry remains significantly incomplete and contains an unacceptably high number of errors. The most appropriate ways to evaluate public safety are general measures, such as homicide, suicide, or violent crime rates, not gun deaths or gun crime. There is no discernible impact on public safety by the firearm program. It is recommended that efforts be focused on more serious threats to public safety, such as terrorists or violent criminals, not normal citizens who own firearms.

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)0.009
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0050.001
Scholarly communication0.0050.003
Open science0.0020.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.098
GPT teacher head0.415
Teacher spread0.316 · 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
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

Citations1
Published2005
Admission routes1
Has abstractyes

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