Measuring and Analyzing the Indicators of Sustainable Urban Housing for Achieving Sustainable Housing Environment (Al-Hindiya Neighbourhood in the Najaf City as Case Study)
Bibliographic record
Abstract
Sustainable urban housing is one of the most important and pressing issues facing cities in the developing world, which has been studied in recent decades in order to achieve sustainability.This research addressed the main factors of sustainable urban housing (diversity, density, sustainable transportation, and social interaction), which contribute to achieving sustainable urban housing.Field surveys, charts and maps, based on geographic information systems, were used to analyze and measure indicators derived from these factors.The practical study was conducted in the Hindiya neighborhood in Najaf, Iraq.This research paper raised the problem of the weak application of sustainable urban housing indicators in residential neighborhoods, this study used an approach that aimed to establish a sustainable urban environment by understanding the fundamental function of determinants and indicators of sustainable urban housing.The study can assist urban planners and engineers to use the research findings as a tool to build sustainable residential areas.The study assumes the existence of a set of factors, indicators and standards through which sustainable urban housing can be achieved.The study's findings revealed that the study area (Al-Hindiya neighborhood) attained an index of service accessibility and an indicator of social contact.Communication and social engagement indicators are also high.This reflects positively on the study area's potential for sustainability.While the study discovered that the mixed use index is low in the study area due to the prevalence of residential use.The research helps to define the physical, social, and economic components of sustainable urban housing, as well as the various purposes it serves.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".