In this report, food distribution is analysed within the context of food systems in Tanzania. This study looks at entry points for further studies of food system issues within the country that will affect progress towards the achievement of Sustainable Development Goal (SDG) 2. Both qualitative and quantitative methods are used, first to map and conceptualize the complexity of the food system in Tanzania, and then to quantify the likely impacts of scenarios of action and inaction.
In Nepal, the Plantwise programme, in collaboration with International Development Enterprises (iDE), has established networks of locally owned plant clinics, run by community business facilitators (CBFs) trained as plant doctors, who provide practical plant health advice. This study examines how gender is integrated into this programme in three purposively selected study districts. It presents the experiences of farmers, the challenges they faced in accessing plant health services through a gender and social inclusion lens.
Geographic information system (GIS) data is often used to map socio-economic data with a spatial component. This data, which is obtained from multiple open-source databases, complements official statistics and generates additional spatial inputs to statistical and econometric analyses. IFAD uses impact assessments using data from face-to-face interviews in order to determine the impact of their projects on strategic goal and objectives. However, the COVID-19 pandemic meant these interviews could no longer take place.
The co-creation and sharing of knowledge among different types of actors with complementary expertise is known as the Multi-Actor Approach (MAA). This paper presents how Horizon2020 Thematic-Networks (TNs) deal with the MAA and put forward best practices during the different project phases, based on the results of a desktop study, interviews, surveys and expert workshops. The study shows that not all types of actors are equally involved in TN consortia and participatory activities, meaning TNs might be not sufficiently demand-driven and the uptake of the results is not optimal.