Enhancing urban local community identity in Iran based on perceived residential environment quality
Bibliographic record
Abstract
Local communities in Iranian cities had a special place in the past and the inhabitants of each local community considered themselves a member. With the introduction of modern urbanisation, the pre-modern structures of the local community have disappeared, but the legal definition of local community has remained as the smallest unit of urban division. Creating a reunion between local community and residents is important, and local identity should also be transformed conceptually. Accordingly, the main purpose of this research is to promote local community identity based on environmental quality indicators. The research has selected the Bagh-Shater local community in Tehran, which conforms to both the historical definition and also the new legal definition of Iranian urban local community. The effect of perceived residential environment quality (PREQ) indicators on urban local community identity (ULCI) has been studied. The results show that although neighbourhood attachment (NA) is an important component of urban local identity, now more than NA, upkeep and care (UC) create a local identity. Based on this, maintenance and preservation of the environment can be seen as a valuable concept which will interconnect the inhabitants and create local environmental behaviours.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".