{"title":"计划评估经验的可借鉴性:铁律、藏匿之手和证据生态系统。","authors":"Tom Ling","doi":"10.1177/0193841X241228332","DOIUrl":null,"url":null,"abstract":"<p><p>Assessing the transferability of lessons from social research or evaluation continues to raise challenges. Efforts to identify transferable lessons can be based on two different forms of argumentation. The first draws upon statistics and causal inferences. The second involves constructing a reasoned case based on weighing up different data collected along the causal chain from designing to delivery. Both approaches benefit from designing research based upon existing evidence and ensuring that the descriptions of the programme, context, and intended beneficiaries are sufficiently rich. Identifying transferable lessons should not be thought of as a one-off event but involves contributing to the iterative and learning of a scientific community. To understand the circumstances under which findings can be confidently transferred, we need to understand: (1) How far and why outcomes of interest have multiple, interacting and fluctuating causes. (2) The program design and implementation capacity. (3) Prior knowledge and causal landscapes (and how far these are included in the theory of change). (4) New and relevant knowledge; what can we learn in our 'disputatious community of truth seekers'.</p>","PeriodicalId":47533,"journal":{"name":"Evaluation Review","volume":" ","pages":"410-426"},"PeriodicalIF":3.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Transferability of Lessons From Program Evaluations: Iron Laws, Hiding Hands and the Evidence Ecosystem.\",\"authors\":\"Tom Ling\",\"doi\":\"10.1177/0193841X241228332\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Assessing the transferability of lessons from social research or evaluation continues to raise challenges. Efforts to identify transferable lessons can be based on two different forms of argumentation. The first draws upon statistics and causal inferences. The second involves constructing a reasoned case based on weighing up different data collected along the causal chain from designing to delivery. Both approaches benefit from designing research based upon existing evidence and ensuring that the descriptions of the programme, context, and intended beneficiaries are sufficiently rich. Identifying transferable lessons should not be thought of as a one-off event but involves contributing to the iterative and learning of a scientific community. To understand the circumstances under which findings can be confidently transferred, we need to understand: (1) How far and why outcomes of interest have multiple, interacting and fluctuating causes. (2) The program design and implementation capacity. (3) Prior knowledge and causal landscapes (and how far these are included in the theory of change). (4) New and relevant knowledge; what can we learn in our 'disputatious community of truth seekers'.</p>\",\"PeriodicalId\":47533,\"journal\":{\"name\":\"Evaluation Review\",\"volume\":\" \",\"pages\":\"410-426\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Evaluation Review\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1177/0193841X241228332\",\"RegionNum\":4,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/18 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Evaluation Review","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1177/0193841X241228332","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/18 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
Transferability of Lessons From Program Evaluations: Iron Laws, Hiding Hands and the Evidence Ecosystem.
Assessing the transferability of lessons from social research or evaluation continues to raise challenges. Efforts to identify transferable lessons can be based on two different forms of argumentation. The first draws upon statistics and causal inferences. The second involves constructing a reasoned case based on weighing up different data collected along the causal chain from designing to delivery. Both approaches benefit from designing research based upon existing evidence and ensuring that the descriptions of the programme, context, and intended beneficiaries are sufficiently rich. Identifying transferable lessons should not be thought of as a one-off event but involves contributing to the iterative and learning of a scientific community. To understand the circumstances under which findings can be confidently transferred, we need to understand: (1) How far and why outcomes of interest have multiple, interacting and fluctuating causes. (2) The program design and implementation capacity. (3) Prior knowledge and causal landscapes (and how far these are included in the theory of change). (4) New and relevant knowledge; what can we learn in our 'disputatious community of truth seekers'.
期刊介绍:
Evaluation Review is the forum for researchers, planners, and policy makers engaged in the development, implementation, and utilization of studies aimed at the betterment of the human condition. The Editors invite submission of papers reporting the findings of evaluation studies in such fields as child development, health, education, income security, manpower, mental health, criminal justice, and the physical and social environments. In addition, Evaluation Review will contain articles on methodological developments, discussions of the state of the art, and commentaries on issues related to the application of research results. Special features will include periodic review essays, "research briefs", and "craft reports".