MétaCan
Menu
Back to cohort
Record W4403706767 · doi:10.1186/s40163-024-00234-6

Crime radiation theory: the co-production of crime patterns through opportunity creation and exploitation

2024· article· en· W4403706767 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCrime Science · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsProduction (economics)BusinessOrganised crimeCriminologyEconomicsSociologyMicroeconomics

Abstract

fetched live from OpenAlex

Abstract Considerable research shows that crime is concentrated at a few proprietary places: addresses and facilities. Emerging research suggests that proprietary places may radiate crime: activities at a place increase the risk of crime in the area around it. Weaknesses in the research create uncertainty about radiation, so we need more rigorous research. To conduct this research, we need a theory of crime radiation that operates at two spatial levels: the proprietary place and the area. This paper describes such a theory. Our theory states that crime radiation stems from the interaction between place management decisions at the place and offenders searching for opportunities in the area. Place managers create crime opportunities inside and outside their places. Offenders exploit place managers’ creations by deliberately searching for opportunities or by chancing upon the opportunities. The ways place managers and offenders interact gives rise to three types of crime radiation: hot dot, veiled dot, and cold dot. Finally, we propose questions crime scientists should answer to better understand crime radiation.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.109
GPT teacher head0.421
Teacher spread0.311 · 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