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Record W2905131167 · doi:10.5555/1480-6800-21.2.141

Building-Related Health Issues in an Unsustainable Neighbourhood– a Study of a Slum Area in Jeddah, Saudi Arabia

2018· article· en· W2905131167 on OpenAlexvenueno aff
Abeer Breengy, Nor’Aini Yusof

Bibliographic record

VenueArab world geographer · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsSlumEnvironmental healthNeighbourhood (mathematics)SocioeconomicsGeographyGovernment (linguistics)Public healthEnvironmental protectionBusinessMedicinePopulationSociology

Abstract

fetched live from OpenAlex

Similar to many slum areas across the globe, the living conditions are very unhealthy, and the people who live in Jeddah slum areas are endangered by contracting certain health complications and diseases. This paper investigated the predominant health issues that are related to the building conditions faced by the people who reside in Kilometre 2, the largest slum area in Jeddah, Saudi Arabia. An online survey was used to collect data from fifty heads of household, selected using a snowballing technique; forty-nine responded. The results revealed that almost all of the respondents acknowledged the bad conditions of the buildings and had no access to clean water. The majority of them experienced building-related health illness, with allergies and dysentery as the most common. The results imply the need for government intervention and a joint effort from the public and private sectors to solve the problems.

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)0.001
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 score0.057
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.323
Teacher spread0.298 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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