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Record W6944061320 · doi:10.18280/ijsdp.200635

Urban Distortion in Classifying Urban Areas Through Residential Zone Redistricting and Land Management Challenges in Najaf City: Diagnosis and Treatment Using GIS to Achieve Sustainability

2025· article· en· W6944061320 on OpenAlexvenueno aff

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityDistortion (music)RedistrictingLand useLand-use planningLand management

Abstract

fetched live from OpenAlex

This study investigated the impact of residential land redistribution on urban growth.It also examined population density management in Najaf by comparing Al-Furat, Al-Amir, and Al-Shurta areas.The study lasted from 2000 to 2023.Re-subdivision methods were examined to determine how they addressed population growth demands and enhanced residential land use distribution.It also explored the planning, social, and economic issues that changed these areas' urban landscapes.Based on the geographical analysis of maps from the investigated years, resubdivision improved land usage and public services, notably in the Al-Furat and Amir areas.Significant re-subdivision rates were 29.63% and 31.58%.Meanwhile, Al-Shurta had little change.Its unique location and residential purpose raised it to 2.75%.The data also showed a definite urban tendency to convert open areas into residential and commercial units, and to alter land use patterns to meet population demands.Spatial analysis was performed using Geographic Information Systems (GIS) and the statistical software SPSS 29.After conducting T-test and ANOVA analysis, significant differences were found for most uses, including residential, which is the focus of our research.The analysis revealed the percentage of urban distortion resulting from residential redevelopment, pressure on services, and the housing ratio.These percentages were achieved at levels less than 0.05, reaching 0.001 and 0.009.They were graded from 2000 to 2023, the periods used for comparison and analysis.This highlights the importance of re-subdividing in urban management and enhancing quality of life.The research concluded that re-subdivision can improve urban fabric if accompanied by a balanced planning framework that considers environmental conservation and provides adequate infrastructure to meet future population growth.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.279
Teacher spread0.248 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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