Modeling Collective Wisdom at the Experimental Level: A Multiple Case Study

Document Type : Original Article

Author

Ph.D. in Sociology, Study of Social Issues in Iran, Shahid Beheshti University, Tehran, Iran.

Abstract
The main goal of this research is modeling of collective wisdom in experimental levels. The research method is multi-instrumental case study and to select cases from the Chalabi stratification system, to collect data from a semi-structured interview, and according to the nature of the topic and research questions, the Boolean technique was used to analyze the data. In order to empirical modeling and find intersections and differences between theoretical and experimental patterns using Boolean Algebra technique, first by extracting and identifying related causal conditions in each of the four areas that are displayed in the form of truth tables, the experimental core pattern in each of the four social domains was analyzed and examined from the perspective of the interviewees and also in whole in their place. then, integrated model of research at the theoretical level was compared with the combined model at the experimental level. The findings indicate that the cognitive diversity is essential for the emergence and strengthening of collective wisdom Over and above that, realization and strengthening of the collective wisdom in different domains of a society needs different preconditions. In the economic domain, real competition as well as reducing government interventions, in the political domain, serious participation and existence of a national government, in the social domain, strong inter-groups relations across society as well as lack of political dominance over civil society, and finally in the cultural domain, prevalence of the norms of fairness, honesty, and truth-seeking in the society and discursive relations are needed.

Keywords


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  • Receive Date 24 February 2025
  • Revise Date 15 May 2025
  • Accept Date 15 May 2025
  • First Publish Date 15 May 2025
  • Publish Date 21 November 2024