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Record W7043339147

The Social Costs of Gun Ownership: Gun Control Policy and Crime

2021· article· en· W7043339147 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueValpoScholar (Valparaiso University) · 2021
Typearticle
Languageen
FieldEngineering
TopicPulsed Power Technology Applications
Canadian institutionsnot available
Fundersnot available
KeywordsHomicideGun controlLegislationPoison controlInjury preventionControl (management)Suicide prevention
DOInot available

Abstract

fetched live from OpenAlex

This paper investigates the impact of gun control legislation on the homicide rate across two countries -the US and Canada.The Brady Act from the US creates the national background check system we use today, while the Firearms Act from Canada starts a new national background check system along with labeling certain guns as "restricted" or "banned" for civilian purchase 12 .For each of these policies, I created a regression that predicts the state's or province's homicide rate based on the policy, year, alcohol consumption, police per capita, and many demographic variables to measure the policy's short-term and long-term impact on the firearm homicide rate.Based on these regressions, both acts significantly decreased firearm homicides in the long-term, but the Brady Act had a bigger impact in relation to the current firearm homicide rate at the time.Therefore, the Brady Act was more effective than the Firearms Act.One main future direction with this research is to analyze homicides caused by other means during the same timeframe.Additionally, since firearm homicides significantly decreased with these acts, it would be valuable to know if firearm suicides also decreased. II.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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