Comprehensive Planning of Urban Housing in Metropolises by Focusing on Urban Integrated Management
Bibliographic record
Abstract
Many scholars of urban studies believe that the most important factor effective on the amount of individuals' welfare is housing. Population increase of Iran and the expansion of the range of cities in Iran in recent decades cause centralization and increase in population densities in Iran and it seems that during recent years, economic policies of housing, as the interface ring for spatial planning policies of lands and urban and rural development, has been to some extent neglected by Iran's planning officials. Considering the multidimensionality of the issue of housing, for urban housing planning the intervention of different state and urban organizations is required and the lack of a comprehensive and integrated management is tangible in this issue. Regarding the domination of municipalities over internal issues of cities and also regarding geographical, political, economic and social conditions of different cities, municipalities can burden the responsibility of this issue. The objective of the present study is to investigate the problem of housing in Iran and providing an appropriate strategy for resolving this issue. Accordingly, the study, by doing library research, administering interviews and consulting state authorities and elites of housing markets and also by using the authors' scientific and executive experiences, an organizational structure was suggested for solving the housing issue. Then, by preparing questionnaires and surveying three groups (citizens, state and municipality authorities and academic specialists) this structure was evaluated using matrix QSPM and the SWOT model. Finally, by using the conducted surveys, the desired strategies were presented for improving the performance of organizational structure.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".