I’ve worked with the RHoMIS survey for over a year now, built close to thirty applications, and worked with research teams in over twenty countries. Yet my trip to Uganda last week was my inaugural experience with applying the tool in situ. The trip gave me a first-hand experience of some of the challenges and nuances of local application of a survey.
Scientists and development practitioners around the world are working with smallholder farmers to transform their agricultural practices to better adapt to, and even mitigate, climate change. The international development community has prioritized two strategies in this regard - increasing the sale of crop and livestock products through increased market participation (commercialization) and increasing the number of crop and livestock species on-farm (diversification).
However, little is known as to the gendered impacts of these changes and specifically, whether these strategies may intensify inequalities between men and women.
Around the world, agricultural development organizations often struggle with surprisingly weak adoption of innovations that had previously been successful at other places. If all goes well, the smallholder farmers addressed by a development program readily adopt and adapt newly introduced practices, such as improved management of crops and livestock. Not so rarely, however, promising innovations do not fit with local culture, cause extra labor at times when the farmers are already extremely busy, or show other unexpected downsides in the new context.
Avoiding locally unsuitable interventions and designing better agricultural development programs by working closely with the local community is possible, of course. But participatory research can take a long time, and results are sometimes biased towards the local opinion-leaders, who are not always the most successful farmers. Could there not be a simpler way to find out “what works” under specific local conditions?
Dahari, an NGO working in the Comoros islands, aims to shape sustainable and productive landscapes with Comorian communities. This local NGO contacted the RHoMIS team in order to better understand their beneficiaries and to measure the impacts of their projects. Earlier this month, I travelled to the Comoros to train the enumerators that were going to be using the survey.
While my work typically focuses on the analysis of RHoMIS data and the development of “back-end” systems, this trip was a fantastic opportunity for me to better understand the farmers behind the data and to gain a deeper understanding of the data collection process. I wanted to write this blog to describe the effort that goes into designing the RHoMIS survey and explain the important role that enumerators play in both survey design and data-collection.
Simon is a PhD candidate hosted by the International Livestock Research Institute and Wageningen University & Research. His research areas include ‘environmental impact assessment’ and ‘food and nutrition security’ in rural communities.
Each entry in the RHoMIS database provides a small insight into the life of a rural household. Research teams go to great lengths to make these snapshots in time as true to life as possible. We design the study – ‘localising’ the survey tool, setting an appropriate sample size and randomising the selection of households. We train a team of interviewers – providing a common understanding of each survey question. Then in implementing the survey, we travel long distances off the beaten track – by foot if necessary – having very personal discussions with rural households two to three times a day for weeks if not months at a time.
Despite these efforts, some aspects of these ‘snapshots in time’ get distorted – resulting in imperfect representations of the rural households’ inputs, outputs, characteristics or wellbeing.
A shared article from the RHoMIS team, based in Bristol, UK and Quito, Ecuador. We write reflections and updates on the development and impact of the RHoMIS tool.
As 2018 turned into 2019, the RHoMIS servers continued to spin and process data from rural households around the world. We are excited to announce that on Wednesday 9 January, the total number of households in the RHoMIS database passed the 20,000 milestone.
The actual number is 21,024 rural households, gathered from 27 countries. More than just a number, these statistics represent a quality and breadth of data that allow for scientific analysis and improved and informed development interventions.
The RHoMIS community of practice is made up of RHoMIS users and creators from across the world. Here we share their stories of how RHoMIS is helping to record and analyse household data.