{"title":"贡献分析中的因果索赔","authors":"M. Palenberg","doi":"10.3138/cjpe.75428","DOIUrl":null,"url":null,"abstract":"This article is a tribute to John Mayne’s work on Contribution Analysis. It focuses on the causal claims Contribution Analysis aims to address, and on how these have evolved since the approach was first published by John in 1999. It first sets out four types of causality with relevance for Contribution Analysis: counterfactual, generative, INUS, and probabilistic causation. It then describes how John integrated the INUS condition and probabilistic elements into the Contribution Analysis approach, followed by how John’s thinking evolved regarding the question of whether the approach could—and should—also address counterfactual questions. The article concludes with observations on how Contribution Analysis can flexibly integrate elements from different causality types.","PeriodicalId":43924,"journal":{"name":"Canadian Journal of Program Evaluation","volume":" ","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Causal Claims in Contribution Analysis\",\"authors\":\"M. Palenberg\",\"doi\":\"10.3138/cjpe.75428\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article is a tribute to John Mayne’s work on Contribution Analysis. It focuses on the causal claims Contribution Analysis aims to address, and on how these have evolved since the approach was first published by John in 1999. It first sets out four types of causality with relevance for Contribution Analysis: counterfactual, generative, INUS, and probabilistic causation. It then describes how John integrated the INUS condition and probabilistic elements into the Contribution Analysis approach, followed by how John’s thinking evolved regarding the question of whether the approach could—and should—also address counterfactual questions. The article concludes with observations on how Contribution Analysis can flexibly integrate elements from different causality types.\",\"PeriodicalId\":43924,\"journal\":{\"name\":\"Canadian Journal of Program Evaluation\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Canadian Journal of Program Evaluation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3138/cjpe.75428\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Program Evaluation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3138/cjpe.75428","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
This article is a tribute to John Mayne’s work on Contribution Analysis. It focuses on the causal claims Contribution Analysis aims to address, and on how these have evolved since the approach was first published by John in 1999. It first sets out four types of causality with relevance for Contribution Analysis: counterfactual, generative, INUS, and probabilistic causation. It then describes how John integrated the INUS condition and probabilistic elements into the Contribution Analysis approach, followed by how John’s thinking evolved regarding the question of whether the approach could—and should—also address counterfactual questions. The article concludes with observations on how Contribution Analysis can flexibly integrate elements from different causality types.