Urban Reconstruction in the Historic Urban Fabric: Towards an Integrated Urban Model
Bibliographic record
Abstract
This study aims to develop a comprehensive framework for urban reconstruction in the Qaliyat district, which has suffered extensive damage due to recent conflicts.As one of Mosul's oldest neighborhoods, Qaliyat holds a unique urban fabric that reflects the city's rich historical and cultural layers.Its strategic location near the Tigris River and the historic center of Mosul makes it a key focus for reconstruction efforts, given its vital role in restoring the urban identity and reviving the collective memory of its residents.The research introduces a specialized analytical tool to document and assess the urban fabric, concentrating on key indicators such as the distribution of spatial activities, topographical analysis of movement networks, levels of openness and enclosure, and an accessibility index that measures how well-connected the area is.Using advanced Geographic Information Systems (GIS) techniques supported by field surveys, the study accurately maps the typical housing units and urban patterns, capturing the detailed characteristics of the historic urban fabric Furthermore, the proposed model was rigorously tested and validated through quantitative measures, including accessibility metrics, network analysis, and catchment area analysis.The results were also compared with real-world data like local traffic flows and community survey responses, ensuring the model's reliability and suitability for practical application.The findings reveal that improving the main road network and redistributing service, educational, and religious functions based on sustainability principles significantly contributes to revitalizing the district's identity and reintegrating it into the urban fabric.These conclusions align with previous research emphasizing the importance of balancing cultural heritage preservation with urban development in post-conflict contexts.The proposed model embodies the principle of "reviving the whole through the part," where gradual reconstruction strategies foster a sustainable urban environment that reconnects the district with both its past and its future.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".