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Record W3191245184 · doi:10.3138/cjccj.2021-0013

A Tale of Two Theories: Whither Social Disorganization Theory and the Routine Activities Approach?

2021· article· en· W3191245184 on OpenAlexaffvenueabout
Jen-Li Shen, Martin A. Andresen

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsProperty crimeCriminologySociologySocial theoryEthnic groupPositive economicsSocial scienceViolent crimeEconomics

Abstract

fetched live from OpenAlex

Social disorganization theory and the routine activities approach have been extensively applied separately as theoretical frameworks for the spatial analysis of crime, with general support. As hypothetical explanations for complex social phenomena, criminological theories can impact how studies are framed and how the crime problem is approached. Thus, it is important to evaluate theories continuously in various geographical, as well as contemporary contexts. This study uses both theories in tandem to examine their ability to explain 2016 property crime in Vancouver, Canada, using 2016 census data. Both theories found moderate support. Of particular note is that all of the variables designated as proxies for ethnic heterogeneity in social disorganization theory were either not statistically significant or negative, consistent with the immigration and crime literature. Additionally, almost all variables, when statistically significant, were found to have consistent results across crime types. These results bode well for the continued use of social disorganization theory and the routine activity approach in spatial analyses of crime.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.005
Science and technology studies0.0050.072
Scholarly communication0.0110.030
Open science0.0030.008
Research integrity0.0060.012
Insufficient payload (model declined to judge)0.0060.001

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 head0.065
GPT teacher head0.329
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2021
Admission routes3
Has abstractyes

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