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Record W4382238662 · doi:10.1080/07352166.2023.2195664

The efficacy of statutory public hearings for planning: A comparison of four Canadian jurisdictions

2023· article· en· W4382238662 on OpenAlexafffundabout
Aaron Alexander Moore, Alexandra Caporale

Bibliographic record

VenueJournal of Urban Affairs · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of Winnipeg
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsStatutory lawOpposition (politics)Public administrationPolitical scienceUrban planningPublic participationWork (physics)Public involvementPublic relationsLawPoliticsEngineering

Abstract

fetched live from OpenAlex

Statutory public hearings for urban development proposals are among the oldest venues for public participation in urban planning in the U.S., Canada, and many other jurisdictions, and the most common venues for resident participation in planning. A number of scholars discuss public hearings in their work. However, such depictions are often contradictory and do not test nor examine whether public hearings allow residents to influence planning decisions. This paper tests the efficacy of statutory public hearings and examines whether institutional difference (at-large vs. ward-based councils) and contextual difference (suburban municipalities vs. their urban cores) affect residents’ ability to influence municipal councilors via public hearings. The paper finds that resident opposition to development at public hearings does not result in substantial changes to development proposals. However, contextual and institutional differences do alter how councilors respond to resident opposition.

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)0.009
metaresearch head score (Gemma)0.034
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 score0.918
Threshold uncertainty score0.594

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0130.008
Scholarly communication0.0050.001
Open science0.0030.005
Research integrity0.0010.002
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 head0.079
GPT teacher head0.344
Teacher spread0.265 · 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

Citations2
Published2023
Admission routes3
Has abstractyes

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