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Record W4281662286 · doi:10.18280/ijsdp.170313

Urban Growth and Its Impact on the Housing Problem: The City of Al-Amarah as a Model

2022· article· en· W4281662286 on OpenAlexvenueno aff
Qassim Mutar Abad Alkhalidy, Murtadha Mudhefer Shar Al-Kaabi

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsUnderemploymentUrbanizationUnemploymentPovertyPopulation growthPublic housingEconomicsPopulationEconomic growthEconomic shortageDevelopment economicsGovernment (linguistics)Sociology

Abstract

fetched live from OpenAlex

The research aims to show the problem of housing as a result of the growing population growth by knowing the amount of housing needed and the housing deficit. The study employed the city of Al-Amarah as a case study and focused on three housing sectors that included 54 residential neighbourhoods, as the city occupies an area of 4854,2 hectares. The study shows the causes of this problem are represented by steady urban growth with a growth rate of 3.4%, which was reflected in the size of families, which amounted to 115,509 families, with a housing density of 24.4 families/ha, living in 72,186 housing units with an occupancy rate of 8. The findings show that another reason is the spread of slums in the city, amounting to 5029 housing units. Finally, the study also shows that as long as the present political and economic difficulties remain unsolved, the urbanisation crisis, which is characterised by unregulated unemployment, underemployment, housing shortages, a lack of social infrastructure, and, of course, poverty, will continue to deteriorate.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.034
GPT teacher head0.305
Teacher spread0.271 · 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 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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