MétaCan
Menu
Back to cohort
Record W2949130712 · doi:10.36939/cjur/vol28no1/art164

Defending Suburbia: Exploring the Use of Defensive Urban Design Outside of the City Centre

2019· article· en· W2949130712 on OpenAlexafffundvenueabout
Cara Chellew

Bibliographic record

VenueCanadian journal of urban research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsArchitectureUrban designProperty (philosophy)Control (management)Public spaceOrder (exchange)Space (punctuation)SociologyArchitectural engineeringPolitical scienceEngineeringGeographyBusinessComputer scienceManagementArchaeologyEconomics

Abstract

fetched live from OpenAlex

Defensive urban design, also known as hostile, unpleasant, or exclusionary architecture is an intentional designstrategy that uses elements of the built environment to guide or restrict behaviour in urban space as a form ofcrime prevention, protection of property, or order maintenance. It often targets people who use or rely on publicspace more than others, like people who are homeless and youth, by restricting the behaviours they engage in.From benches specially designed to prevent lying down to the addition of elements that are meant to deterskateboarding, forms of defensive design vary according to the behaviour it is intended to restrict. While muchof the current research on the subject privileges the urban centre as the site of research, this paper expands thefocus from the centre to the periphery. Taking two public spaces in Toronto’s inner suburb of North York as astarting point, this paper examines how defensive urban design is used regulate, control, and maintain publicspace outside of the city centre.

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)0.004
metaresearch head score (Gemma)0.004
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 score0.230
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.403
GPT teacher head0.341
Teacher spread0.061 · 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

Citations21
Published2019
Admission routes4
Has abstractyes

Explore more

Same venueCanadian journal of urban researchSame topicUrban Planning and GovernanceFrench-language works237,207