Promoting the Social Cohesion in the Traditional Cities
Bibliographic record
Abstract
There are two dominant concepts about traditional cities, first, the physical traditional environments reflect the lifestyle form of their individuals and vice versa. that means, in one respect, the urban traditional form explains and supports the unity of the society’s nature which is manifested in social cohesion. Second, those cities with their societies are able to preserve themselves over time, in spite of forces of change. So, the paper is interested in exploring the mutual relationship between the physical built environment and social cohesion in traditional cities as the socio-spatial Phenomenon. Its problem is that some development projects for traditional cities do not care about social cohesion and do not deal with these cities as one of the socio-spatial types. The paper's question is, how can additions and development projects enhance and promote social cohesion in Traditional cities? The hypothesis of the paper is that social cohesion results from seven factors that pressure individuals to be under a relatively clear and defined social Order, these are (Customs, kinship, values and ethics, law, interests and conflicts, responsibilities, and rights) and that there is correlative compatibility between the phenomenon of social cohesion and the features of the physical Built environment for traditional cities. The project of developing the traditional city of Kadhimiya in Baghdad was taken as a case study, The paper concluded that all urban environments have seven factors, but their arrangement is what determines the socio-spatial Type. The results of the project’s assessment weren't suitable to promote the traditional socio-spatial type, but it was promoting the modern type according to the arrangement of its seven factors. So, there is a special arrangement for traditional cities that must be taken into account in any addition or urban development.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 0.001 |
| 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".