Cultural norms can thwart the most technically sound development strategies. How can the cultural consensus model, developed by anthropologists, help to ensure that culture strengthens rather than weakens a strategy’s effectiveness?
This blog post has been adapted from an article in Journal of Social Science & Medicine – Population Health.
If you’ve worked in development for long enough, at some point you’ve scratched your head about why a technically sound strategy achieved less than expected results. As the old business adage goes, “Culture eats strategy for breakfast.” Sometimes proven strategies become breakfast because culture is not identified or factored into planning. Culture here means the shared knowledge, norms, beliefs, and values of a group of people. Culture can promote or thwart results from interventions in ways we never considered. Remember the 2014 Ebola outbreak in West Africa? The technical strategy was to isolate sick people and avoid contact with their bodily fluids, especially from a person who had just died. But initially, the strategy did not factor in the populations’ strong values of family, which manifested in people caring for sick family members and washing the bodies of their dead. These norms were a significant factor in transmission of the virus, and understanding the culture was key to the curtailment.
Culture can vary widely among not just different groups of people, but also between subgroups. One of the challenges we as development practitioners face in planning interventions is understanding the cultural nuances around those interventions. Anthropologists recognized that in our accelerating world, it’s not always possible or efficient to sit in a village and observe a population for a couple of years to identify its culture. Thus, they developed the cultural consensus model (CCM) to timely identify key norms, values, and beliefs of groups. Chemonics and Arizona State University (ASU) anthropologists have partnered to form the Global Impact Collaboratory (GIC), a space for innovation that has piloted the CCM in international development projects in Haiti, Mozambique, and the West Bank and on diverse topics such as climate change, justice, and gender-based violence.
The CCM is a survey that uses convenience sampling of the target population to produce information about culture and can identify cultural variations in population subgroups. Examples of results from the CCM include determining what a culture believes are hygienic behaviors that people should or should not engage in, or identifying beliefs about birthing practices among medically trained and traditional birth attendants. The CCM is not used to measure behaviors. It is relatively quick to assemble and administer; the survey takes about 15 minutes per individual and requires about 30 respondents per topic, per population subgroup. Typically, formulating the survey involves desk research of the relevant literature from which survey questions are drafted, a focus group of the target population to review the draft questionnaire, and then the usual steps in testing the questionnaire to finalize the items. Analysis of the responses can be done in the software package UCINET or a version of the R programming language developed for the CCM.
GIC applied the CCM in three USAID projects. In the first, we examined knowledge and attitudes around promoting adaptation in coastal areas in Mozambique; in the second, we looked at a population’s beliefs about when they should use informal or formal justice mechanisms for a justice project in Haiti; and third, we examined norms and values about gender-based violence and divorce in the West Bank of Palestine.
We used three different groups of enumerators for data collection. In Mozambique, we connected with a local university and taught professors and their students about the model, then used the students as the enumerators. In Haiti, we subcontracted a local research firm; and in Palestine, we used staff from the project, interested NGOs, and government ministries. In all three places, we trained the enumerators in the methodology as well as in data collection and issued them a certificate from ASU acknowledging they had been trained in the CCM; this recognition award from a U.S.-based university was a significant motivator for the participants. By training local students and professionals in the CCM, we promoted the sustainability of its use in these locations.