Capital Transfer through Transmitting Towns Consistent with the Talibanism View in Architecture and Urban Planning
Bibliographic record
Abstract
The concentration of facilities, services and activities in an area leads to massive migration in the territory and neglect of existing capacities and resources in the territory, which is a critical situation in the long run. If the location of the capital is not correct, it will cause problems whether in terms of defense and security or in terms of natural resources and urban infrastructure, not only for the capital but also for the whole country. In this study, we seek to examine the situation of Kabul as a capital city and provide proposed solutions to improve the current situation and the possibility of moving the capital. For this purpose, the required information was collected using a documentary study, available information, and the latest master plan of Kabul city, which was carried out by Russia in 1964. Due to the lack of financial resources and the political situation in Afghanistan, it is suggested to transfer the capital to Parwan by planning new cities with a limited population. The new towns, are designed according to the culture of the citizens of Afghanistan and with the thinking of Talibanism in architecture and urban planning. These new towns are at certain distances from each other, next to the main road and fruitful arteries between Kabul and Parwan city, and finally, the capital will be transferred to Parwan. In that case, we will have the capital with a limited population that will reduce any risk and enable political control.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".