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Record W4372348757 · doi:10.18280/ijsdp.180411

Urban Resilience and Poverty in Malaysia

2023· article· en· W4372348757 on OpenAlexvenueno aff
Nor Suhadah Salleh, Nor Fatimah Che Sulaiman, Suriyani Muhamad, Mohd Nasir Nawawi, Nazli Aziz, Mohd Azlan Shah Zaidi

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
FundersMinistry of Higher Education, Malaysia
KeywordsResilience (materials science)PovertyEnvironmental planningUrban resilienceGeographyUrban povertyEnvironmental resource managementUrban planningEconomic growthEnvironmental scienceEconomicsCivil engineeringEngineering

Abstract

fetched live from OpenAlex

This article is a systematic review paper that focuses on urban resilience studies in Malaysia.Generally, resilience is not a new concept that has attracted scholars to conduct numerous relevant studies.Unfortunately, the majority of earlier studies did not consider the urban resilience perspectives towards poverty in Malaysia.This article utilizes three journal databases, Scopus, Web of Science, and MyCite for the review of the current research.The Transparent Reporting of Systematic Reviews and Meta-Analyses method known as Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was adopted in this article.As a result, 10 articles have been systematically studied as a result of the search efforts.Most crucially, the review was able to develop four key topics based on thematic analyses, including economic resilience, social resilience, environmental resilience, and institutional resilience.However, there are still limited numbers of literature available on urban community resilience in Malaysia and also literature on community resilience towards poverty as compared to studies on resilience towards disaster.In short, the finding of this study hopefully can be a good baseline for the related stakeholders and policymakers in formulating action plans and strategies related to urban and poverty planning in the upcoming years.

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 score0.246
Threshold uncertainty score0.185

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 head0.015
GPT teacher head0.291
Teacher spread0.276 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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