GENNOVATE’s research design builds on the approach developed and refined by three World Bank global studies, Voices of the Poor, Moving Out of Poverty, and On Norms and Agency. The methodology features a comparative case study method, qualitative data collection sensitive to local circumstances, standardization of instruments, and purposive sampling techniques. Together these elements allow broad patterns to be detected without losing their grounding in local contexts and realities.
The analytic approach is informed by a conceptual framework based in feminist and innovation theories and the notion of agency-opportunity structure interactions (see Concept note for further discussion). The study is guided by the following research questions:
· How do gender norms and agency advance or impede innovation capacity and technology adoption in agriculture and NRM across different contexts?
· How do new agricultural technologies affect gender norms and agency across different contexts? Under what conditions can technologies do harm?
· How are gender norms and women’s and men’s agency changing, and under what conditions do these changes catalyze innovation and adoption, and lead to desired development outcomes? What contextual factors influence this relationship?
To address these questions, GENNOVATE uses a community-level case-study approach. A case refers to a social group living in a single locality that the inhabitants call their village, community, or hamlet. In each research village, field teams apply a standardized package of seven data collection instruments which include a mix of focus groups, semi-structured individual interviews, key informant interviews, and a literature review. Study participants include equal numbers of women and men. The tools were piloted in villages in Mexico and Uganda; and three regional training of trainer events prepared the PIs for managing the fieldwork. Data collection began April 2014 and will conclude in 2015.
The data analysis plan features in-depth case study techniques to explore the study questions holistically in specific contexts. This is combined with variable-oriented qualitative analytic techniques that draw on GENNOVATE’s coded dataset. A major data coding exercise is underway with teams based in Mexico and Peru who are using a well- known type of social science software (QSR NVivo).