A presentation on the mapping of social network architecture of rural communities gender & technological innovations in the semi-arid tropics of India.

6. 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.”

7. 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.

8.  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

10. Mapping the social network architecture of
rural communities

11. Kanzara
Aurepalle

12. 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

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Sample size : Aurepalle – 410 (1868); Kanzara – 319 (1190)

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17.  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

18. 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

19. 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

20. 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

22. 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

23. Network map of sample men for all
transactions
Network map of sample women for all
transactions

24.  Evolution of networks through mentoring
 Dependence relations and dependency
networks
Source of actors, power; exploitative, oppressive,
tactics

26. 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

27. 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

28.  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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33. Concerns

34. 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

35. 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

37. 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

38. 
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39. 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.

40. 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.

41. 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

42. 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

43. ICRISAT is a member of the CGIAR Consortium