The role of social capital in shaping religious conflict: A study of Islamic communities in Pasuruan regency, Indonesia
Bibliographic record
Abstract
Religious conflict remains a pressing issue in plural societies, particularly where political and social tensions intersect with religious identity. In Indonesia, one of the world’s largest Muslim-majority countries, understanding the drivers of religious conflict at the local level is vital for fostering social cohesion. This study investigates the role of social capital—specifically bonding, bridging, and linking—in influencing religious conflict in Pasuruan Regency, East Java, with particular attention to the mediating roles of political and social conflict. Using a quantitative approach, data were collected through structured face-to-face interviews with 400 respondents, selected using multi-stage sampling. Structural Equation Modeling (SEM) via SmartPLS was employed to analyze both direct and indirect relationships between the constructs. The results reveal that bonding and bridging significantly reduce political and social conflict, which in turn significantly reduce religious conflict. However, their direct effects on religious conflict are not significant. Linking was found to significantly reduce social conflict but did not show a significant influence on political or religious conflict directly. Indirect effect analysis confirmed that bonding, bridging, and linking can mitigate religious conflict through their effects on political and social tensions. This study contributes to the growing literature on social capital and conflict by highlighting the importance of indirect pathways. Practically, the findings suggest that policies aiming to reduce religious conflict should strengthen both horizontal (bonding and bridging) and vertical (linking) social ties, while also addressing underlying political and social grievances. The study underscores the need for integrated, community-based conflict prevention strategies.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".