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Record W4309076324 · doi:10.1080/13549839.2022.2145602

Exploring perspectives on sustainability and planning from national and local planners for effective practice: the experience of Ghana

2022· article· en· W4309076324 on OpenAlexaff
Hsi‐Chuan Wang

Bibliographic record

VenueLocal Environment · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsUniversity of Toronto
FundersWashington University in St. Louis
KeywordsSustainabilitySettlement (finance)Local planningEnvironmental planningTask (project management)Urban planningBusinessPolitical scienceEconomic growthManagementEngineeringGeographyEconomicsCivil engineering

Abstract

fetched live from OpenAlex

Understanding how the planning system is (not) functioning remains a challenge for many urban planners in the developing world. This paper responds by conducting an analysis of the discourse between national and local planners. It seeks to unfold the challenges of informal settlement planning in Accra, Ghana. Through in-depth interviews, this paper suggests that: (I) Grounding sustainability must be conducted by implementing the plans rather than producing the plans. (II) Empowering local planners should be a primary task to incrementally remedy the challenging planning system in countries like Ghana.

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)0.011
metaresearch head score (Gemma)0.012
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 score0.027
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.026
Scholarly communication0.0060.006
Open science0.0010.007
Research integrity0.0020.005
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 head0.049
GPT teacher head0.303
Teacher spread0.254 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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