The Role of Mosque to Avoid Violent Extremism: A Comparative Study of Eastern and Western Countries
Bibliographic record
Abstract
The present project aims to conduct a comparative study between Eastern and Western countries on the role of mosques to avoid violent extremism in society analyzing their functioning. The purposes of the study are to explore the link between mosques and extremism and to draw a policy outline to avoid violent extremism. This is a qualitative study including formal and informal interviews, observations, and secondary data. Theoretically, the concept of Avoid Violent Extremism has been described in the light of a theory, Iannaccone and Berman’s (2006) Religious Extremism, and traced the relevant situation in the Pakistani context. Lahore, Karachi, Peshawar, and Quetta are the target cities from the Eastern side while Ottawa, New York, Paris, and London are from the Western side. This study reveals that sectarianism is deeply rooted in Pakistani mosques, variety in internal control systems, and lack of administerial regulations. In Western countries, there is scope for the training of Imams with the administerial checks on the performance of mosques and Imams, and promoting nationalism. This project outlines a Nation Action Plan to incorporate the role of mosques in the welfare of the country and to avoid violent extremism and promote community resilience.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".