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Participatory action research (PAR) is an approach to research that prioritizes the value of experiential knowledge for tackling problems caused by unequal and harmful social systems, and for envisioning and implementing alternatives. PAR involves the participation and leadership of those people experiencing issues, who take action to produce emancipatory social change, through conducting systematic research to generate new knowledge. This Primer sets out key considerations for the design of...
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This paper explores the thinking and practice of ‘action inquiry’ an embedded learning practice that can help navigate complexity when practising change together. The paper uses examples from social contexts where there are concerns about community wellbeing and health care. These are drawn from collaborative or collective leadership development programmes within public services that seek to bring new attention to the qualities of how people think, converse and interact, as part of their...
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Abstract Background: Program logic is one of the most used tools by the public policy evaluator. There is, however, little explanation in the evaluation literature about the logical foundations of program logic or discussion of how it may be determined if a program is logical. This paper was born on a long journey that started with program logic and ended with the logic of evaluation. Consistent throughout was the idea that the discipline of program evaluation is a pragmatic one, concerned...
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This article explores the potential of using participatory action research as an adaptive programming modality to drive learning and innovation to tackle the drivers of (and seek to eliminate) the Worst Forms of Child Labour. We draw on our experience from early phases of implementation of a large-scale action research programme, which despite the constraints covid-19 posed in moving to full implementation and participatory engagement with children and other stakeholders on the ground, is...
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Achieving impact through research for development programmes (R4D) requires engagement with diverse stakeholders across the research, development and policy divides. Understanding how such programmes support the emergence of outcomes, therefore, requires a focus on the relational aspects of engagement and collaboration. Increasingly, evaluation of large research collaborations is employing social network analysis (SNA), making use of its relational view of causation. In this paper, we use...
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Despite a wide body of literature on the importance of program theory and the need to tackle complexity to improve international development programming, the use of program theory to underpin interventions aimed at facilitating change in complex systems remains a challenge for many program practitioners. The actor-based change framework offers a pragmatic approach to address these challenges, integrating concepts and frameworks drawn from complexity science and behavioral change literature...
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Despite increased discussions in the community and a common understanding about the virtue of mechanism-based explanation, little is known about the true benefits and challenges of applying causal mechanism analysis in practice. This chapter aims to introduce the reader to the topic of causal mechanisms and synthesize significant findings on this special issue. It begins by laying out definitions and concepts of causal mechanisms in evaluation literature and proposes a two-way classification...
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Realist evaluation and experimental designs are both well-established approaches to evaluation. Over the past 10 years, realist trials—evaluations purposefully combining realist evaluation and experimental designs—have emerged. Informed by a comprehensive review of published realist trials, this article examines to what extent and how realist trials align with quality standards for realist evaluations and randomized controlled trials and to what extent and how the realist and trial aspects...
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Evaluators who take a complexity-aware approach must consider tradeoffs related to theoretical parsimony, falsifiability, and measurement validity. These tradeoffs may be particularly pronounced with ex-post evaluation designs in which program theory development and monitoring frameworks are often completed before the evaluator is engaged. In this chapter, we argue that theory-based evaluation (TBE) approaches can address unique ex-post evaluation challenges that complexity-aware evaluation...
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The United Kingdom Research and Innovation (UKRI) Global Challenges Research Fund (GCRF) aimed to address global challenges to achieve the United Nations (UN) Sustainable Development Goals through 12 interdisciplinary research hubs. This research documents key lessons learned around working with Theory of Change (ToC) to guide Monitoring, Evaluation and Learning (MEL) within these complex research for development hubs. Interviews and document reviews were conducted in ten of the research...
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The investigation of causal mechanisms has the capacity to provide donors and implementing institutions with a greater understanding of people's reasoning and reactions as they work with interventions. This chapter contributes to the literature by identifying behavioral mechanisms generated through engagement with climate-resilient agriculture interventions within a larger livelihood project in Ethiopia. It works through the steps that enabled the study to unpack the black box between the...
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Applied agricultural research institutes play different roles in complex agricultural innovation processes, contributing to them with other actors. To foster learning and usable knowledge on how research actions influence such lasting innovation processes, there is a need to identify the causal mechanisms linking these actions and the effects of the changes they enable. A participatory, theory-driven, ex-post evaluation method, ImpresS, was developed by the French Agricultural Research...
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While many knowledge workers may fear that the rise of artificial intelligence (AI) will threaten their jobs, this article argues that small evaluation businesses should embrace AI tools to increase their value in the marketplace and remain relevant. In this article, consultants from a research, evaluation, and strategy firm, Intention 2 Impact, Inc., make a case for using AI tools to disrupt business as usual in evaluation from theoretical and practical perspectives. Theoretically, AI may...
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Realist evaluation has, over the past two decades, become a widely used approach in evaluation. The cornerstone of realist evaluation is to answer the question: What works, for whom, under what circumstances, and why. This is accomplished by explicating the causal mechanisms that, within a particular context, generate the outcomes of interest. Despite the central role of mechanisms in realist evaluation, systematic knowledge about how the term mechanism is conceptualized and operationalized...
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