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Record W4392062386 · doi:10.54097/by681011

A Statistical Study of Crime Rate in Suburban British Columbia

2023· article· en· W4392062386 on OpenAlexaboutno aff
Sun Dawei

Bibliographic record

VenueJournal of Education Humanities and Social Sciences · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsForensic engineeringCriminologyGeographyStatisticsEngineeringSociologyMathematics

Abstract

fetched live from OpenAlex

This study examines the correlation between various factors and crime rates in four regions in British Columbia, Canada. The study focuses on both positive and negative correlators and ranks them based on the strength of their correlation coefficients. The positive correlators include immigrant population percentage, single-parent families, unemployment rate, religious population percentage, and population without employment income. The negative correlators are related to income levels, including the percentage of working population with high annual income, median and average employment income. The study finds that income levels have a strong negative correlation with crime rates, while immigration and certain social structure factors have a positive correlation. However, this study does not establish a causal relationship between these factors and crime rates. The findings suggest the need for further research to understand the specific nature of the relationship between immigration and crime rates, considering contextual factors such as wealth, income level, and employment status of immigrants.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.155
GPT teacher head0.430
Teacher spread0.275 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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