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Governing the Sick City: Urban Governance in the Age of Emerging Infectious Disease

2007· article· en· W2043286226 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAntipode · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCorporate governanceMetropolitan areaGlobalizationContext (archaeology)Political sciencePolitical economyPublic administrationDevelopment economicsEconomic growthSociologyGeographyLawBusinessEconomics

Abstract

fetched live from OpenAlex

Based on a case study of the 2003 severe acute respiratory syndrome (SARS) outbreak in Toronto, Canada, this article suggests that we may have to rethink our common perception of what urban governance entails. Rather than operating solely in the conceptual proximity of social cohesion and economic competitiveness, urban governance may soon prove to be more centrally concerned with questions of widespread disease, life and death and the construction of new internal boundaries and regulations just at the time that globalization seems to suggest the breakdown of some traditional scalar incisions such as national boundaries in a post-Westphalian environment. We argue that urban governance must face the new (or reemerging) challenge of dealing with infectious disease in the context of the "new normal" and that global health governance may be better off by taking the possibilities that rest in metropolitan governance more seriously.

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)0.001
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 score0.031
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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

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 head0.035
GPT teacher head0.385
Teacher spread0.350 · 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