Towards a Modern Design of Undeveloped City Using a Spatial Modelling Analysis; a Case Study of Irbid City in Jordan
Bibliographic record
Abstract
In the past, Jordanian cities were just small centers, with no planning systems.Today, many of these cities have expanded in response to emergency urbanization and ongoing political crises.The resulting development has irreversibly modified the urban landscape.Studies of urban conditions in Jordanian cities, particularly, Irbid, are key to understanding how rapid growth has altered its architectural and urban landscape.This paper focuses on the problem of urban regeneration and requalification to identify the variables driving informal development in Irbid.Understanding the real factors, as illegal and abusive land use, at play versus unnatural development where classical approaches are not suitable for understanding the problem.Highlighting policies, strategies, and tools needed to identify transformation trends of cities like Irbid, to produce hypothesis of sustainable and suitable development.Results show that to propose innovative hypothesis we must first research evolution mechanisms and their transformation effects.Using tools that define conditions of under developing that govern transformations in our case study.A spatial modelling would be an interpretation model that combines effects and causes, of the cited under developing situation in future projection of sustainable development.The proposed spatial modelling, "Integral Planning Model" (IPM), throw investigations and interviews and simulations try to build a parametric matrix processing able to help the planners and policy makers to put up suitable strategies.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".