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Record W4393316288 · doi:10.1177/09754253241230636

Learning from the Policy and Practice of Green City Development in Phnom Penh, Cambodia

2024· article· en· W4393316288 on OpenAlexaff
Dolorès Bertrais, Laura Beckwith

Bibliographic record

VenueEnvironment and Urbanization Asia · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsUrban planningContext (archaeology)Sustainable developmentCitizen journalismPovertyPolitical scienceCapital cityEnvironmental planningEconomic growthSociologyEnvironmental ethicsGeographyCivil engineeringEconomicsEngineering

Abstract

fetched live from OpenAlex

The complex challenge of managing urban growth and development in the context of climate and environmental change has led to a proliferation of policy discourses related to the ‘green city’. While useful as a buzzword, it is argued that green city discourses often overlook or even mask questions of social and environmental justice. This case study of Phnom Penh, Cambodia, shows that the presence of green and sustainable city discourses in policymaking does not reflect the reality of urban planning practices. Instead, it has produced an urban vision reflective of the priorities of global capital while contributing to the ongoing destruction of urban biodiversity and the marginalization of urban residents living in poverty. It is argued that a reconceptualization of the green city be undertaken, which incorporates understanding of participatory and distributive justice to ensure that urban planning practices are inclusive and sustainable.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.011
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

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