Investigating the Relationship between Social Capital and Tribal Divergence in Mamsani and Rostam Counties - Soheila Lashkari; Asghar Mirfardi; Habib Ahmadi; Aliyar Ahmadi (توسعه اجتماعی, 2024)
Traditional communities are faced with local divergence and convergence. Considering the diversity of tribes in Mamsani and Rostam cities, this article examines the relationship between social capital and its dimensions with tribal divergence in the Mamsani and Rostam counties in 2022. Using the survey method, a structured questionnaire used for data collection. The study sample was 450 residents of Mamsani and Rostam counties that selected using a multi-stage cluster random sampling method. The factor analysis and Cronbach's alpha used to evaluate the validity and reliability of the questionnaire, respectively. The data collection tool was a standard questionnaire. To measure social capital, the questionnaire of Mirfardi and Valinejad (2018) was used, and to measure tribal divergence, the researcher-made questionnaire was used. Face validity was used to measure the validity of the questionnaire and internal consistency using Cronbach's alpha method was used to determine the reliability of the questionnaire. Data were analyzed using SPSS software. The findings showed that there is a significant negative relationship between social capital and tribal divergence. The findings showed that there is a significant negative relationship between social capital and its dimensions (except normativeness) and tribal divergence. Social capital components (interpersonal trust, normativeness, social relations, social participation and institutional trust) showed different relationships with tribal divergence among the tribes living in Mamsani and Rostam cities. Given there was significant difference between the tribal divergence of women and men, and significant difference was observed between the tribal divergence according to education and people with higher education had less tribal divergence. Multivariate regression of the independent variables explained nearly 31% of the variance of the dependent variable.