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Record W2907096791 · doi:10.4324/9781351299886-8

Homicide In Canada

2017· book-chapter· en· W2907096791 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

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHomicide, Infanticide, and Child Abuse
Canadian institutionsnot available
Fundersnot available
KeywordsHomicideCriminologyPsychologyMedicineMedical emergencyPoison controlInjury prevention

Abstract

fetched live from OpenAlex

This chapter describes the incidence and characteristics of homicide in Canada by focusing on three sources of variation: temporal, spatial, and social. It begins by tracing trends in Canadian homicide rates from the 1920s through the 1980s. The chapter evaluates recent concerns over rising levels of homicide from the perspective of trends over several decades. It discusses spatial variation in homicide rates: the distribution of homicide across regions and communities of different sizes. The chapter examines the distribution of homicide among social groups distinguished by gender, race, and age. It addresses the growing fears of Canadians that patterns of homicide in Canada are coming to resemble those in the United States—not just in levels, but also in some characteristics. The chapter draws on both legal and non-legal criteria in its analysis of homicide in Canada. Regardless of gender or race, age will shape the likelihood of involvement in homicide either as victim or as offender, though in somewhat different ways.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.944
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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

Quick stats

Citations38
Published2017
Admission routes1
Has abstractyes

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