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Meeting the United Nations Sustainable Development Goals (SDGs) will require adapting or redirecting a variety of very complex global and local human systems. It is essential that development scholars and practitioners have tools to understand the dynamics of these systems and the key drivers of their behavior, such as barriers to progress and leverage points for driving sustainable change. System dynamics tools are well suited to address this challenge, but they must first be adapted for...
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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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Background: Addressing today’s sustainability challenges requires adopting a systemic approach where social and ecological systems are treated as integrated social-ecological systems. Such systems are complex, and the international development sector increasingly recognises the need to account for the complexity of the systems that they seek to transform. Purpose: This paper sketches out the elements of a complexity-aware monitoring and evaluation (M&E) system for international...
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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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This chapter focuses on facilitation given by the Innovation Caucus to provide expert academic critique to inform Innovate UK's strategy for UK business innovation. As Innovate UK's strategy developed, it became evident that several policy domains needed critical insights and evidence. An academic critical friend provided the latest academic insights, evidence and wider perspective of the actors in the UK Innovation system, insights of which policy makers often lack. The chapter gave case...
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Development and radical uncertaintyFeinstein, O. - 2020 - Development in Practice, 30(8), 1105–1113
Development strategies, programmes and projects are designed making assumptions concerning several variables such as future prices of outputs and inputs, exchange rates and productivity growth. However, knowledge about the future is limited. Uncertainty prevails. The usual approach to deal with uncertainty is to reduce it to risk. Uncertainty is perceived as a negative factor that should and can be eliminated. This article presents an alternative approach which recognises that radical...
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Knowledge management strategies are important for firms’ competitive positioning. This paper examines how knowledge management codification and personalisation strategies are developed in response to environmental and organisational dynamics in an international non-governmental organisation. A longitudinal case study of the organisation’s strategic reformulation of its KM strategy over a 2.5 period is drawn upon. The research examines how pressures in the firm’s operating environment led to...
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Issues of power are not new to program evaluation. What is new is a consideration of how programming uses insights into incentives that shape and adapt implementation. How should one evaluate in a way that explicitly assesses the ways in which a program considers power? One of the innovative topics deriving from the democracy and governance space is the approach of thinking and working politically (TWP) which is seeing increased use in development programming. TWP suggests different mental...
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Over the past decade, the field of development evaluation has seen a renewed interest in methodological approaches that can answer compelling causal questions about what works, for whom, and why. Development evaluators have notably started to experiment with Bayesian Process Tracing to unpack, test, and enhance their comprehension of causal mechanisms triggered by development interventions. This chapter conveys one such experience of applying Bayesian Process Tracing to the study of citizen...
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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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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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This chapter explores the use of mechanisms within the realist evaluation of the Building Capacity to Use Research Evidence (BCURE) program, a £15.7 million initiative aiming to improve the use of evidence in decision-making in low and middle-income countries. The evaluation was commissioned to establish not just whether BCURE worked but also how and why capacity building can contribute to increased use of evidence in policymaking in the very different contexts in which the program operated....
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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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Introduction:The Most Significant Change (MSC) technique is a complex-aware monitoring and evaluation tool, widely recognized for various adaptive management purposes. The documentation of practical examples using the MSC technique for an ongoing monitoring purpose is limited. We aim to fill the current gap by documenting and sharing the experience and lessons learned of The Challenge Initiative (TCI), which is scaling up evidence-based family planning (FP) and adolescent and youth sexual...
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This chapter argues that the credibility of causal mechanisms can be greatly increased by formulating them as statements that are both empirically falsifiable and empirically confirmable. Whether statements can be so depends on the potential availability of the relevant evidence (e.g., no evidence exists that can prove or disprove the existence of God, but good quality evidence is potentially available in many other cases). The Bayes formula can be used to measure the extent to which a given...
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Experimental evaluations—especially when grounded in theory-based impact evaluation—can provide insights into the mechanisms that generate program impacts. This chapter details variants of experimental evaluation designs and also analytic strategies that leverage experimental evaluation data to learn about causal mechanisms. The design variants are poised to illuminate causal mechanisms related to program implementation and the contribution of selected components of multifaceted programs....
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This article explores the challenges of monitoring and evaluating politically informed and adaptive programmes in the international development field. We assess the strengths and weaknesses of some specific evaluation methodologies which have been suggested as particularly appropriate for these kinds of programmes based on scholarly literature and the practical experience of the authors in using them. We suggest that those methods which assume generative causality are particularly well...
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This chapter examines good practices in implementing effective Monitoring, Evaluation, and Learning (MEL) systems within complex international development Democracy, Human Rights, and Governance (DRG) programs, which are characterized by challenges of non-linearity, limited evidence of theories of change, and contextual and politically contingent nature of outcomes. The chapter presents three cases of MEL systems in complex projects implemented by Pact across distinct and diverse operating...
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Realist evaluation is an approach with a strong emphasis on causal mechanisms and the context in which they are triggered. However, recent reviews of published realist evaluations show that context is often understudied. This is problematic, as a thorough understanding of the relationship between context and causal mechanisms is crucial in assisting policymakers to make appropriate and targeted decisions that improve the intervention. Therefore, we set out to test whether combining realist...
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