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Record W2279043625 · doi:10.4337/9781783479641

Cities and Partnerships for Sustainable Urban Development

2015· book-chapter· en· W2279043625 on OpenAlexaboutno aff

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2015
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLocal Economic Development and Planning
Canadian institutionsnot available
Fundersnot available
KeywordsSustainable developmentEnvironmental planningUrban planningGeographyBusinessRegional scienceEconomic geographyPolitical scienceEngineeringCivil engineering

Abstract

fetched live from OpenAlex

Over the past two decades, sustainability has become a principal concern for city administrators. It is a more than just environmental entailing economic, demographic, governance, social, and amenity aspects. After a short introduction to some theory, this book provides broad coverage of these aspects and their manifestations in Asia, Africa, Europe and North America. The contributors discuss, in detail, topics surrounding measurement, growth strategy, citizen participation, revitalization, and competitiveness. Though each of the cities discussed – ranging from Shanghai, to Barcelona, to Montreal – are distinct, there are similarities that connect them all. The book highlights their common elements to provide a feasible outcome for sustainable 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.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.005
Scholarly communication0.0120.008
Open science0.0010.011
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0300.008

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 head0.102
GPT teacher head0.275
Teacher spread0.173 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2015
Admission routes1
Has abstractyes

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