The Sustainable Defensive Space in Neighborhoods with Different Planning Patterns - A Comparative Analytical Study in Iraq
Bibliographic record
Abstract
Cities are undergoing continuous morphological transformations, resulting in a contrast between the planning patterns of residential neighborhoods with traditional organic fabrics and modern grid patterns.This study aims to understand urban morphological transformations and their impact on security and sustainability in cities, focusing on the relationship between urban planning patterns (organic and grid) and the concept of "sustainable defensive space."The research is grounded in a theoretical framework that combines Neuman's defensive space theory and Heller and Hanson's space syntax theory, providing a basis for analyzing how city structural characteristics influence urban security.The study used a quantitative and qualitative analytical methodology.It was conducted in two adjacent residential neighborhoods in Babylon.The data from plans, aerial photography, and field visits.The analysis aims to measure characteristics such as integration, connectivity, control, and street network depth to identify differences in "sustainable defensive space" between different planning patterns.The study concludes with practical recommendations for urban planners to enhance the design of residential neighborhoods in Babylon and other cities with similar contexts, aiming to improve security, social cohesion, and environmental sustainability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".