Sustainable urban regeneration through cultural diversities, Tehran, Iran
Bibliographic record
Abstract
Background and objectives: Urban regeneration is a clear mirror that reflects urban thinking and planning in every national system. This process in Iranian cities is quite different from the other cities in the world. Many factors have been important in this process, but a major issue was socio cultural groups and nationalities like it has seen and studied at Montreal, Canada by author. The aim of this paper is to reconsider city sustainable development theory by analyzing urban regeneration processes with emphasis on cultural diversity or internal ethnic groups in Tehran. Methods: An analytical-qualitative framework is used to acquire an understanding of the specifications involved. Through impartial observations on two cities (Tehran and Montreal) over more than five years, this paper attempts to understand the effects of cultural-ethnic groups as social capitals on changing urban spaces. Findings: The results revealed that there are not any real multicultural cities in Iran and Tehran is a sample of local-internal multicultural city which its people are not serious social capitals or human forces in urban planning, implementation, and changes. Therefore, cultural capitals, which are consequential to urban regeneration process, as in the case of Montreal, have not been formed in Tehran . Conclusion: These findings may provide urban policy-makers in Iran and Tehran with social important facts for regeneration planning development, which helps to improve social capitals of cultural-ethnic groups.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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 teacher head, 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".