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Record W3120620395 · doi:10.1111/cag.12671

After the downturn: Perceptions of crime and policing in the southeastern Saskatchewan oil patch

2021· article· en· W3120620395 on OpenAlexaffvenueabout
Christopher D. O’Connor, Rick Ruddell

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of ReginaOntario Tech University
Fundersnot available
KeywordsBoomLaw enforcementOil boomIndustrialisationPerceptionEnforcementRecessionCriminologyResource cursePolitical scienceGeographyPsychologyEconomicsNatural resourceLawEngineering

Abstract

fetched live from OpenAlex

The relationship between crime and the rapid growth and industrialization associated with resource‐based booms in large boomtowns is well‐documented. This study focuses on changes in police‐reported crime and perceptions of crime and disorder in a region experiencing a mini‐boom after the boom subsides. Analyses of survey results of 1,336 respondents living in oil‐impacted and non‐impacted communities in southeastern Saskatchewan reveal several noteworthy differences between these two groups. Inconsistent with prior research, respondents in the oil‐impacted region were less fearful of being victimized than their counterparts in non‐impacted communities and did not believe that a lack of law enforcement was a problem. Our analyses also revealed that the economic downturn after oil prices and production plunged was associated with significant decreases in rates of reported crime, crime severity, and traffic collisions. Implications for establishing a more comprehensive theory of the boom‐crime relationship and future research are discussed.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.104
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.170
Teacher spread0.166 · 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 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

Citations13
Published2021
Admission routes3
Has abstractyes

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