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Record W2556422168 · doi:10.1080/02723638.2016.1255920

Geography of crime in a Brazilian context: an application of social disorganization theory

2016· article· en· W2556422168 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

VenueUrban Geography · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsSimon Fraser University
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsContext (archaeology)CensusGeographyUnit (ring theory)Property crimeEconomic geographyRegional scienceSocial geographyCriminologyLatin AmericansProperty (philosophy)Social environmentHuman geographySociologySocial scienceViolent crimePolitical scienceDemographyArchaeologyPsychologyLawEpistemology

Abstract

fetched live from OpenAlex

Geography of crime research dates back to the early 1800s, most of which in English and in the context of the United States and Europe, but with a growing and significant literature studying the developing world. We contribute to this literature through an application of social disorganization theory in a Latin American context: Campinas, Brazil. We consider a number of property and violent crime types using census tracts as the spatial unit of analysis. Implementing a spatial regression method, we find support for social disorganization theory, but not as strong as similar studies in Europe and North America. However, because of the context of Campinas, Brazil, a different understanding of the local conditions proves to be important for understanding the geography of crime in this context. The implications of these results are discussed in the context of theoretical developments as well as crime prevention initiatives.

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)0.000
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 score0.115
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.010
GPT teacher head0.292
Teacher spread0.282 · 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