Small farmers offer a diversity of perspectives on agricultural production strategies. On one hand, individual knowledge and beliefs may be quite similar across perspectives, such as the idea that crop rotation is an important practice. On the other, broad based knowledge and belief systems can be markedly different. Specifically, farmers may gravitate towards conventional, risk-averse, or conservation agricultural perspectives. These overarching strategies shape multiple indicators of one's perception of best farming practices. Although research often finds differences in mindset according to region, little scholarship has examined agroecological perspectives as a function of gender. This paper investigates an ethnically homogenous agricultural zone in north central Mali with equal samples of males and females within each of four villages. Our goal is to explore gender differences by focusing on: (a) examining variations in gender perspectives with respect to agroecological knowledge and belief systems, (b) exploring gender differences within and across villages and, (c) analyzing the social network to identify actors that foster relationships based on farmers' gender.

1. Gender differences in agricultural
production strategies:
Variations by village and social
network MATT FORNITO VIRGINIA TECH/OIRED
KEITH M. MOORE VIRGINIA TECH/OIRED
MOUSSA KEITAINSTITUT D’ECONOMIE RURALE/CRRA-
MOPTI
EMILY VAN HOUWELING VIRGINIA TECH/OIRED

2. Agenda
 Conservation Agriculture
 Mindsets
 How gender affects mindsets
 Social network analysis (SNA)
 How gender shapes network relationships
 Implications and practical uses of SNA

3. Overview
 Conservation Agriculture Production Systems (CAPS)
 Resistance to Adoption
 Changing Mindsets
 Gender Differences
 Relationships

4. Goals
Identify relationships between farm men, farm women, and
non-farm agents and their respective mindsets
 Identify what gender differences exist across mindsets and network
structures.
 Identify what village differences exist across mindsets and network
structures.
How can researchers and agents better
communicate/promote Conservation Agriculture?

5. Sample
Mali
 N=238
 Farmers from Two Cercles (Cercle of Koro and Cercle of Bankass)
containing Four Villages (Koporo-pen, Oro, Diallassagou, and
Lagassagou)
 Equal gender sampling (Men n=118; Women n=120)
 Snowball sampling from farmers to obtain 36 non-farm agents (service
sector or community agents)

6. Factor Analysis
 The Agricultural Production Perspectives Scaleis a 20-item
questionnaire that assesses farming ideologies and practices.1
 Exploratory factor analysis (EFA) was conducted in SPSS on the farm men
sample and then again on the farm women sample
 Items were retained based on item loadings, cross loadings, and
communalities
 Factor loadings were retained if they had an eigenvalue greater than one
and verified produced through Cronbach alpha scale reliability
 Both farm men and farm women produced a two-factor solution comprised
of primarily, unique item loadings

7. Farm Men Factors
A two-factor solution with six different items emerged for the farm men. The
items composing the first factor are beliefs associated with a “mixed crop
livestock production” including:
 Inorganic fertilizer is best to improve soil quality
 Timely weeding (before setting of seed) is important to a successful harvest
 Crop residues should only be fed to livestock and poultry
 Land preparation for crop production begins with plowing
The second factor that emerged for farm men can be described as “capital
intensive” agriculture based on the beliefs that:
 Applying chemical pesticides is always necessary
 Farm labor should be replaced by more efficient herbicides and machines

8. Farm Women Factors
Factor analysis for farm women produced a two-factor solution comprised
of seven items. The first factor can be described as a traditional “market
driven” approach and contains three items:
 Planting decisions are always based off of current market prices
 Crops should only be grown for sale
 Earning off-farm income is more important than a large harvest
The second factor was considered “sustainable production” and contained
four items:
 One should maintain a permanent crop cover
 Farm production is necessary to feed the family
 Inorganic fertilizer is best to improve soil quality
 One should always strive to grow the most on one’s land

9. Group Differences
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
Sustainable Production
Market Driven
Capital Intensive
Mixed Crop Livestock Production
Factor Analysis of Farmer and Non-Farm Agents Mindsets
Farm Men Farm Women Non-Farm Agents

10. Gender Differences by Farmer Contact
Location
Average Number of Contacts
Information Resource
Women
Koro (n=60) 4.37c 2.23b
Bankass (n=60) 4.70d 3.93c
Men
Koro (n=58) 3.24b 2.19b
Bankass (n=60) 1.38a 1.00a

11. Social Network Analysis
 Network analysis is a tool used to
map all individuals and their
relationships within a defined space
 Helps to identify clusters, density of
network, highly connected individuals,
and isolates
2

12. Social Network Analysis
Visual graphing tool with mathematical calculations in the background
 Individuals (actors/nodes)
 Relationships (ties/lines)
Measures
 Degree Centrality
 Authorities

13. Utility of Social Network Analysis in
Agricultural Communities
 Advise Seeking
 Mindset Change

14. Farm Men
Network
Farm Women
Network
Authority of Nodes within the Network
LAGASSAGOU
DIALLASSAGOU
KOPORO-PEN ORO
LAGASSAGOU DIALLASSAGOU
KOPORO-PEN ORO

15. Farm Men and Women in Koporo-pen
Farm Women
Network in
Koporo-Pen
Farm Men
Network in Koporo-Pen

16. Conservation
Agriculture
Level of agreement/
disagreement with statement:
“Tillage causes land degradation”

17. Tillage by Gender

18. Take Away
 External agents looking to change mindsets should learn and identify the
value systems of locals to adapt change mechanisms to the population at
hand
 Intervention are different based on the village and person-influence
 Men and women have mindset differences and hold different relationships
in a network
 There is an opportunity to target key players in a network to more
effectively promote new technologies and ideas like CA

19. Thank You.

20. Citations
1. Lamb, J., Moore, K. M., & Christie, M. E. (2010). Research framework for
technology network and gendered knowledge analyses. Blacksburg, VA.
2. http://blog.luisdaniel.com/wp-content/uploads/2013/10/SocialNetwork-
1024x723.png