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Record W2050030846 · doi:10.1080/00330124.2014.970843

The Pen or the Sword: A Situated Spatial Analysis of Graffiti and Violent Injury in Vancouver, British Columbia

2014· article· en· W2050030846 on OpenAlexaffabout
Blake Byron Walker, Nadine Schuurman

Bibliographic record

VenueThe Professional Geographer · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Spaces through Art
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGraffitiSituatedContext (archaeology)Interpersonal violenceGeographyPublic spaceSociologyPoison controlCriminologyHuman factors and ergonomicsArchaeologyVisual artsArtMedicineEngineeringComputer science

Abstract

fetched live from OpenAlex

Graffiti is a ubiquitous feature of the urban landscape commonly perceived to be a symptom of disorder, deprivation, and violence. Broken windows theory asserts that it is also a cause. To examine this, we conduct a geographic correlation study of graffiti and violence using geographic information systems. A strong spatial covariation is observed, with spatially dependent residual clusters suggesting that the graffiti–violence relationship is context dependent and varied. Ferrell and Weide's spot theory provides a lens for situating hot spots and facilitating a more nuanced interrogation of graffiti and violence in several Vancouver neighborhoods. We advocate for situated spatial analyses of interpersonal violence to inform public health interventions and advance policymaking beyond the popular aesthetic symbolism of urban space.

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)0.002
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 score0.035
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0040.002
Scholarly communication0.0030.000
Open science0.0010.002
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 head0.008
GPT teacher head0.290
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

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

Citations26
Published2014
Admission routes2
Has abstractyes

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