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Record W2027587633 · doi:10.1177/0013916514540459

The Relationship Between Dwelling Type and Fear of Crime

2014· article· en· W2027587633 on OpenAlexaffabout
Heather Rollwagen

Bibliographic record

VenueEnvironment and Behavior · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFear of crimeFortress (chess)Space (punctuation)Social psychologyPsychologyEveningSociologyCriminologyHistory

Abstract

fetched live from OpenAlex

Urban sociologists and criminologists have maintained housing’s importance in providing individuals with a sense of security within their neighborhood. Yet it remains unclear whether all types of housing provide this sense of safety in the same way. This article provides an analysis of the relationship between dwelling type and fear of crime. Data from the 2009 Canadian General Social Survey are analyzed. Results suggest that living in a multiunit dwelling has no statistically significant impact on fear of crime in the neighborhood; however, individuals living in high-rise and low-rise residences are less likely to be fearful of crime while at home in the evening. One possible explanation for these findings is the fortress effect: High-rise buildings isolate individuals in physical space, providing security in the home, and creating physical and social distance from the rest of the neighborhood. The implications of these findings 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)0.003
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 score0.238
Threshold uncertainty score0.474

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.092
GPT teacher head0.347
Teacher spread0.255 · 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

Citations43
Published2014
Admission routes2
Has abstractyes

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