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Background: Ex-post evaluation of sustainability has been done for 40 years in global development. However, it has been done far less than 1% of all global development projects, for there is little proof that “sustainable” development is or is not. Similarly, foreign aid projects are implemented to foster sustainability, but without the benefit of evidence from expost evaluations of what drove it and limited research on the benefits of robust exit strategies. Purpose: Transparency in values...
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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 are interested in capturing how things causally influence one another. They are also interested in capturing how stakeholders think things causally i...
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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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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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Large publicly funded programmes of research continue to receive increased investment as interventions aiming to produce impact for the world’s poorest and most marginalized populations. At this intersection of research and development, research is expected to contribute to complex processes of societal change. Embracing a co-produced view of impact as emerging along uncertain causal pathways often without predefined outcomes calls for innovation in the use of complexity-aware approaches to...
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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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Research for development (R4D) funding is increasingly expected to demonstrate value for money (VfM). However, the dominance of positivist approaches to evaluating VfM, such as cost-benefit analysis, do not fully account for the complexity of R4D funds and risk undermining efforts to contribute to transformational development. This paper posits an alternative approach to evaluating VfM, using the UK’s Global Challenges Research Fund and the Newton Fund as case studies. Based on a...
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The complexity of issues addressed by research for development (R4D) requires collaborations between partners from a range of disciplines and cultural contexts. Power asymmetries within such partnerships may obstruct the fair distribution of resources, responsibilities and benefits across all partners. This paper presents a cross-case analysis of five R4D partnership evaluations, their methods and how they unearthed and addressed power asymmetries. It contributes to the field of R4D...
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“Hacking by the prompt”—writing simple yet creative conversational instructions in ChatGPT's message window—revealed many valuable additions to the evaluator's toolbox for all stages of the evaluation process. This includes the production of terms of reference and proposals for the dissemination of final reports. ChatGPT does not come with an instruction book, so evaluators must experiment creatively to understand its potential. The surprising performance of ChatGPT leads to the question:...
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Large language models (LLMs) are a type of generative artificial intelligence (AI) designed to produce text-based content. LLMs use deep learning techniques and massively large data sets to understand, summarize, generate, and predict new text. LLMs caught the public eye in early 2023 when ChatGPT (the first consumer facing LLM) was released. LLM technologies are driven by recent advances in deep-learning AI techniques, where language models are trained on extremely large text data from the...
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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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MEL4 Adaptive Management
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