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Record W1965945439 · doi:10.1068/c10158

Achievements and Opportunities in Initiating Governance for Urban Sustainability

2012· article· en· W1965945439 on OpenAlexaboutno aff
Riley Smith, Arnim Wiek

Bibliographic record

VenueEnvironment and Planning C Government and Policy · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsnot available
Fundersnot available
KeywordsConceptualizationSustainabilityCorporate governanceGovernment (linguistics)Variety (cybernetics)VitalityPublic administrationPolitical scienceEnvironmental planningBusinessPublic relationsGeographyFinanceComputer science

Abstract

fetched live from OpenAlex

The concept of urban sustainability governance has developed as an institutional guiding concept to holistically address the vitality of cities under a long-term perspective and is based on the collaborative efforts of government, administration, business, science, and the civil society. Yet, the initiation and implementation of this guiding concept faces a variety of barriers, including deficient conceptualization, unfamiliarity, detrimental organizational structures, and inertia. We examine the initiation of urban sustainability governance in the City of Richmond, British Columbia, Canada. On the basis of the reviews of administrative documents and interviews with staff across various administrative levels and units, we reflect on achievements and shortcomings against guidelines of urban sustainability governance spelled out in the literature. Our study indicates accomplishments in the conceptualization of a vision and overall framework to operate from, but also a number of deficits in specifying sustainability targets, applying governance principles, and evaluating impacts. Additionally, we discuss how administrative structures influence how urban sustainability governance is being implemented. We draw conclusions regarding general factors for succeeding in the initiation and implementation of urban sustainability governance.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.361

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 head0.074
GPT teacher head0.367
Teacher spread0.293 · 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

Citations44
Published2012
Admission routes1
Has abstractyes

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