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Mapping the social network architecture of rural communities gender & technological innovations in the semi-arid tropics of India

  1. Introduction What my study is all about SOCIAL STRUCTURE Peter Blau (1975) identifies three major approaches to social structure: as a configuration of social relations and positions, as the substratum that underlines all of the social life and history, and “ multidimensional space of the differentiated social positions of the people in a society or other collectivity.”
  2. Introduction SOCIAL NETWORK THEORY Social Structure focus is on the social structure as a system of social relations deals rather with the very structure of their relations—how are they organized in a pattern of relationships. And this is why the social network theory which is essentially the study of how the social structure of relationships around a person, group, or organization affects beliefs, behaviors and outcomes becomes important and relevant in understanding social structure.
  3.  Effect of the network and not the strength or weakness of the network  Situated in a risky, harsh, vulnerable environment  Gender and technology focus  Whole networks Q2
  4. Mapping the social network architecture of rural communities
  5. Kanzara Aurepalle
  6. Implementing a survey in village Aurepalle Village censuses using semi structured interviews mapping social networks – detailed registries of women and men - individual and household level Focus group meeting with women in Kanzara Complementing gender analysis with social analysis understand social networks Multi-generational panel data Tapping the multigenerational long- term data on agricultural and economic change (ICRISAT VLS/VDSA) Innovative quantitative and qualitative analysis of social networks
  7.    Sample size : Aurepalle – 410 (1868); Kanzara – 319 (1190)
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  9.  Studying whole networks Trace information flows in all directions, affect behaviors and attitudes, relationships in different settings  Social network theory as a structural approach  The focus on gender
  10. Kanzara Crowding in the core Less reciprocal ties Degree centrality : 2-85 Aurepalle No crowding in the centre More hubs or focal points More reciprocal ties Degree centrality more than in Kanzara
  11. Kanzara - Closeness measure Crowding in the core More reciprocal ties Hubs – not on caste or class lines Aurepalle - Closeness measure More scattered Changing cultural norms - education, access to urban centre SHGs
  12. Network map of a household, Kanzara Legend: circle – Men; Triangle – Women; Square - organization Red color – inside the village Black color – outside the village; blue color-ego
  13. Legend: circle – Men; Triangle – Women; Red color – alter Blue color – Ego/actor Network map of sample men for all transactions, Kanzara Network map of sample women for all transactions, Kanzara
  14. Network map of sample men for all transactions Network map of sample women for all transactions
  15.  Evolution of networks through mentoring  Dependence relations and dependency networks Source of actors, power; exploitative, oppressive, tactics
  16. 0 5 10 15 20 25 30 35 40 1954 1960-65 1966-70 1971-75 1976-80 1981-85 1986-90 1991-95 1996-2000 2001-2005 Noofrespondents Years Figure1a.Memberships into groups,1954-2005,Kanzara Cooperativeandcreditsociety SelfHelpGroups Others(youth, homeo) 0 10 20 30 40 50 60 70 80 1960-65 1971-75 1976-80 1981-85 1986-90 1991-95 1996- 2000 2001- 2005 Numberofrespondents Years Figure1b. Memberships into groups, 1960-2005,Aurepalle Raithu mitra group-all male Self-Helpgroups-all women Caste group/association Creditsociety/coop Chitfund Toddytapper'sAssociation
  17. The money lender as an important node in other’s network, Aurepalle Legend: circle – Men; Triangle – Women; Square - organization Red color – inside the village Black/blue color – outside the village
  18.  How government policies affect the formation of networks Examples of SHGs and the kinship network; sustainability??  Uniqueness of semi-arid tropics influencing formation of social networks Risky envi, policy bias, infrastructure, agriculture, marginalized, excluded  Social networks and technology adoption Integrated study, identify constraints and opportunities, weak links, gaps etc
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  22. Concerns
  23. Kanzara Few focal nodes – innovators, Early adopters Information spread is through kinship Unidirectional ties Aurepalle Few focal nodes – innovators, Early adopters Social learning Reciprocal ties
  24. 0 10 20 30 40 50 60 70 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 %ofcropproportion Figure 6.1 Area under different crops, Kanzara, 1975-2010 Sum of BENGAL GRAM Sum of BLACKGRAM Sum of CHICKPEA Sum of Cotton Sum of GREENGRAM Sum of GROUNDNUT Sum of PIGEONPEA Sum of SORGHUM Sum of SOYBEAN Sum of WHEAT
  25. Network architecture of the households adopting Maruti variety of pigeonpea Legend: Square – in the village; Triangle – outside the village; Color: blue – UC; red – NT; Pink – Muslim; Black – OBC; Grey – SC; Green - ST
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  27. Conclusions 1. The degree of the social connectedness varies across villages, across different interactions and transactions and across groups and individuals. 2. The density of the networks also vary depending on the characteristics of the region as a result of which people develop interactions and relationships with other individuals, groups and organizations differently. 3. The analysis of social network architectures confirm the assumption that whom one knows is more important than what one knows for benefiting from the networks. 4. The case study on the spread of new agricultural technology through kinship networks leads to the conclusion that in the absence of good governance, favourable policies, and extension services informal social networks come to the forefront and help in the spread of the technology through kin, friends and acquaintances.
  28. Conclusions 4. Women in agriculture are more likely to use these informal networks as they are the custodians of the seed (seed saving and sorting is an activity performed exclusively by them in the SAT regions) as they can communicate, share, and interact with members of their kin by blood or marriage. 5. The study also clearly brings out that networks affect individuals and households differently depending on gender, class, kinship, political power etc 6. Men and women build and form networks differently and use them also differently 7. Expanding the social networks of women by connecting women to weak ties – far-reaching connections can help increase their social capital.
  29. Conclusions 8. Social networks can substitute for formal channel of information and knowledge spread at the village level 9. The sociological analysis based on the network maps documenting key nodes and ties facilitates the identification of strategies to help vulnerable groups to adopt, adapt and increase their levels of resilience. viable entry points for interventions, media for collective action, pathways of information flows, and access to resources and services. Broader context of development  Target where linkages are weak and or missing  In and out migration of ideas and innovations  Interactional infrastructure – shared values and visions
  30. Way forward  The role of institutions in network building  Use statistical tools of analysis and econometrics to complement the descriptive analysis and make the conclusions more robust.  Study from a network perspective:  migration  nutrition and food security  poverty, and non-farm employment opportunities  Class, caste, gender perspectives  Others - Global Vs local links In my next seminar I will be presenting some interesting results on gender and nutrition
  31. ICRISAT is a member of the CGIAR Consortium
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