Integration Theory in Measuring Cultural Diversity in the Western Urban Context: The Case of Islamic Religious Buildings in the Western Urban Context
Bibliographic record
Abstract
This research deals with integration theory in measuring cultural diversity in the urban context.Cultural diversity is the recognition of the rights of all groups in society, so the presence of Muslims in Western society is an example of reflecting cultural diversity in the Western urban context.Integration theory is an attempt to bring a variety of theories and models into one framework.It consists of four quadrants, each quadrant representing a specific scale.Muslims represent the social part interacting with Western society, which is the subjective, individual and collective part of the integration theory (the first and third quadrants), and the Islamic religious buildings and their interaction with the urban context represent the objective part of the integration theory (the second and fourth quadrants).A specific questionnaire is chosen for each quarter and the results of the questionnaire provide a measure of the subjective and objective aspects of integration theory.The results showed that the subjective aspects of individuals and their relationship with Western society are the highest percentage of the objective aspects of the requirements of the Islamic religious building or the relationship of the religious building with the Western urban context.Multicultural planning has a role in integrating culturally diverse societies and achieving smooth interaction among its members.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".