The reason why I love teaching is that the most interesting effects don’t happen in the classroom but afterward, sometimes even years later. One of my first assignments as independent consultant three years ago was to teach an introduction to Social Network Analysis at the International Lifestock Research Institute in Kenya. Yesterday I received an email from a participant with his newest publication on the way that social networks influence farmer’s ability to detect cattle disease.
And I love research that finds out the unexpected: People with just a high number of links in the community don’t have a high knowledge about trypanosomosis – they just know what everybody in the community already knows, repeating the same old same old. Because the knowledge needed is not so much home grown but brought into the community from the outside, it is crucial to connect to those more marginal actors who bring in new knowledge.
And if you are interested in learning more about the farmer’s ability to detect and control trypanosomosis, here is an abstract of the paper:
Impact of social networks on cattle farmers’ knowledge of animal trypanosomosis and its control
Hippolyte Affognon, Der Dabiré, Issa Sidibé and Thomas Randolph
Although there is increasing emphasis on farmer-led extension in rural development and the power of word-of-mouth and social networks for the spread of knowledge and information, few studies have been conducted at farmers’ level to understand the impact a social network has on farmers’ knowledge. This study was undertaken to explore the relationship between a cattle farmer’s position in a community and his or her level of knowledge on animal trypanosomosis and its control. Data were collected through a knowledge, attitude and practices (KAP) survey by use of a questionnaire in four randomly selected villages in the commune of Solenzo in Burkina Faso. A social network at farmer level was constructed that included all cattle farmers in each village. Descriptive analysis and a linear regression model were used to analyze the data. Results showed that the power of a cattle farmer for catching whatever is flowing through the network as information, measured as his degree centrality, is negatively associated with knowledge on animal trypanosomosis and its control. However, a person’s strategic connection to the most marginal people, but exceptional in a specific knowledge in a community — a concept better reflected by a person’s betweenness centrality — is positively associated with knowledge.