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Fringe explosions: risk and vulnerability in Canada's new in‐between urban landscape

2009· article· en· W2064329549 on OpenAlexaffvenueabout
Roger Keil, Douglas L. Young

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsYork University
Fundersnot available
KeywordsVulnerability (computing)UrbanizationGeographyArchetypeService (business)Space (punctuation)Urban landscapeEnvironmental planningEconomic growthEconomy

Abstract

fetched live from OpenAlex

This article argues that a new landscape of urbanization takes shape in Canadian cities. In‐between the old downtowns and the new suburbs of urban Canada, a hitherto underexposed and under‐researched mix of residential, commercial, industrial, educational, agricultural and ecologically protected areas and land uses has become the home and workplace, and increasingly also the playspace of most people in Canada. The article examines this new landscape through the lens of the specific risks and vulnerabilities experienced by its inhabitants and users. Using a propane gas explosion in Toronto in the summer of 2008 as an example, we demonstrate that the ‘in‐between city’ is a space of great complexity, which has grown haphazardly and in a contradictory fashion, where, in contrast to the archetype of inner city and suburb, no clear spatial imaginary has been guiding urban development. This leads to always uncomfortable and sometimes dangerous proximities between various and competing uses and social practices. This is nowhere as clear as it is in the splintered urban infrastructures that service this landscape or use the in‐between city's space to service other adjacent or distant purposes .

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.216
Teacher spread0.206 · 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.

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

Citations23
Published2009
Admission routes3
Has abstractyes

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