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Record W2122970655 · doi:10.2747/0272-3638.29.4.348

At Street Level: Bureaucratic Practice in the Management of Urban Neighborhood Change

2008· article· en· W2122970655 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueUrban Geography · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBureaucracyDiscretionNegotiationEnforcementState (computer science)Public administrationPolitical scienceSociologyLawPolitics

Abstract

fetched live from OpenAlex

Bureaucratic regulation shapes cities in important ways. Yet certain aspects of how state regulation operates in urban neighborhoods have been understudied in geography and cognate disciplines. This article focuses on one understudied group of state actors: property use, health, and liquor inspectors, part of a wider group of "street-level bureaucrats" who, through their face-to-face contact with the public, affect how and where regulatory enforcement gets done. Through a case study of inspectors in Vancouver, British Columbia, this study identifies the role of street-level bureaucratic practice in shaping urban neighborhoods and in managing neighborhood change. We discuss how street-level bureaucrats negotiate the constraints and pressures inherent to their practice while also exercising a degree of discretion. And we argue that these micro-level concerns are important to understanding how cities are produced but they must also be linked with analyses of wider processes that shape contemporary urban development.

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 score0.399
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
Bibliometrics0.0000.001
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 head0.051
GPT teacher head0.287
Teacher spread0.236 · 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