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Record W3087848853 · doi:10.3138/cjccj.2019-0063

Examining Micro-Level Homicide Patterns in Toronto, 1967 Through 2003

2020· article· en· W3087848853 on OpenAlexvenueaboutno aff
Vincent Harinam

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsHomicideGeographyDowntownPoison controlDescriptive statisticsDemographyCriminologyInjury preventionStatisticsSociologyMathematicsMedicineArchaeologyMedical emergency

Abstract

fetched live from OpenAlex

This article assesses the spatial distribution and developmental pattern of micro-level homicide clusters in Toronto between 1967 and 2003. The spatial unit of analysis is the street segment and is defined as the two block faces on both sides of a street between two intersections. Three time periods (1967 to 1979, 1980 to 1989, and 1990 to 2003) covering 1,671 homicides were pooled to ensure sufficient numbers for analysis. Given the qualitative strength of the dataset, a series of descriptive statistics and geospatial statistics are used. Toronto’s developmental homicide pattern is characterized by a dense concentration of single-homicide street segments within the downtown core between 1967 and 1989, with the mass dispersal of multi-homicide street segments across the city between 1990 and 2003. Single-homicide street segments accounted for 84% and 81% of homicides between 1967 and 1979 and 1980 and 1989, respectively. However, multi-homicide street segments tripled between 1990 and 2003, rising from 16% of homicides in the first time period to 45% in the third. This reflects a change in the character of homicides with drug and gang-related homicides increasing in the third time period.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.256
GPT teacher head0.365
Teacher spread0.109 · 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 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

Citations6
Published2020
Admission routes2
Has abstractyes

Explore more

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