Frank Place

Indicators for monitoring and evaluating research-for-development: A critical review of a system in use

Research-for-development (R4D) refers to research activities specifically designed to address critical social, environmental, and economic challenges and improve human well-being. It is essential to have well-designed indicators to monitor and evaluate progress, guide decision-making, and support learning and improvement. This paper reviews and compares two sets of indicators in use by a large international research consortium: i) ad hoc indicators developed by and for individual (non-pooled) projects, and ii) a standard set of indicators designed as part of a common results framework for a new portfolio of research initiatives. We assess both sets of indicators against the SMART (specific, measurable, achievable, relevant and time-bound) criteria, identify common errors in indicator formulation, compare the thematic coverage of the two sets of indicators, and derive lessons for improved indicator formulation. A large proportion of the non-pooled indicators fail to meet the SMART criteria. The indicators in the standard set are stronger, but with scope for improvement, especially in terms of relationship to the result of interest, specification of the indicator, measurability, standardization of outcome indicators, and impact indicators. We recommend having a balanced set of indicators of key outputs, outcomes, and impacts, based on clear and well-defined result statements.

Nurturing soil life through agroforestry: The roles of trees in the ecological intensification of agriculture

How could science–policy interfaces boost food system transformation?

The world’s food systems must be transformed to make healthier diets more accessible for all, while increasing the sustainability and resilience of these systems, as clearly called for in the 2030 Agenda for Sustainable Development. Scientists and policymakers are among the actors necessary for this transformation. This chapter reviews the importance of the interfaces between science and policy and how these interfaces can become more active and effective. There is no single science—policy interface, but rather many, at different scales, for different functions, addressing different challenges. Strengthening, connecting, and streamlining these interfaces can ensure the consistency and success of food system transformation. To improve science—policy interfaces, the scientific community should (1) generate actionable knowledge, data, and metrics to move beyond obstacles, and address trade-offs and barriers to change, including power asymmetry, path dependency, conflicts of interest, and risk and uncertainty; (2) articulate models, knowledge, and place-based innovations for designing, implementing, and assessing specific transformative pathways—this requires specific arrangements, dialogues, and approaches, including scientific ones; (3) connect expertise mechanisms, such as scientific committees, to address multisectoral and multiscale processes for sustainable development; and (4) strengthen scientific cooperation through major challenge-oriented alliances and programs. Science—policy interfaces can play a decisive role if they are able to dovetail divergent views and overcome polarized debates and sectoral fragmentation. These interfaces must also help us to look ahead and to bridge local and global processes and actions.