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Record W4402908302 · doi:10.18535/sshj.v8i09.1356

Sustainable Urban Housing Development in Pakistan Through Planning Mechanism: Challenges and Opportunities

2024· article· en· W4402908302 on OpenAlexaff
Nabel Akram, Wen Chen, Komal Tariq, Zhaosheng Li, Hou Linjun

Bibliographic record

VenueSocial Science and Humanities Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsInternational Political Science Association
FundersNational Social Science Fund of ChinaNational Office for Philosophy and Social Sciences
KeywordsMechanism (biology)Environmental planningSustainable developmentBusinessUrban planningEnvironmental resource managementGeographyEnvironmental sciencePolitical scienceEngineeringCivil engineering

Abstract

fetched live from OpenAlex

The issue of sustainable housing is significant in Pakistan’s cities due to population growth, scarcity of materials, and poor urban planning. This paper aims to explore the challenges of affordable sustainable housing and suggest solutions. Some of the challenges are an increase in informal settlements, environmental impacts from unplanned development, and social vices from poor housing delivery. The main conclusions of the study point to the importance of sound urban management and adaptive planning systems. The paper supports policies on affordable housing through subsidies, microfinance, and PPPs, with a focus on community involvement in planning. Eradicating bureaucracy and corruption is essential for policy enforcement. The study therefore suggests the need to consider the economic, environmental, and social factors to create sustainable urban shelter in Pakistan with the view of enhancing the quality of urban life and sustainability for generations to come. This nine-point strategy is in response to the challenges of rapid urbanization and is for sustainable urbanization.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0010.002
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 head0.152
GPT teacher head0.349
Teacher spread0.197 · 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.

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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