The Causal Mechanism Claim in Evaluation: Does the Prophecy Fulfill?

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Title: The Causal Mechanism Claim in Evaluation: Does the Prophecy Fulfill?
Authors: Schmitt, Johannes1 (AUTHOR) johannes.schmitt@deval.org
Source: New Directions for Evaluation. Fall2020, Vol. 2020 Issue 167, p11-26. 16p.
Subject Terms: Definitions
Abstract: 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 of causal mechanisms along which the chapters to this issue are structured. The chapter continues by introducing the Causal Mechanism Claim and elaborates on how analyzing causal mechanisms is expected to increase policy relevance and causal capacity in evaluations. Drawing on this issue's rich corpus of firsthand practical experience, this introduction synthesizes key lessons that support or contradict the Causal Mechanism Claim. We find that both parts of the claim—increased policy relevance and strengthened causal capacity—are supported by the authors' experiences as bundled in this issue. However, we also identify challenges related to cross‐cutting issues such as communication and practical applicability and point to the importance of method integration. [ABSTRACT FROM AUTHOR]
Copyright of New Directions for Evaluation is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: 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 of causal mechanisms along which the chapters to this issue are structured. The chapter continues by introducing the Causal Mechanism Claim and elaborates on how analyzing causal mechanisms is expected to increase policy relevance and causal capacity in evaluations. Drawing on this issue's rich corpus of firsthand practical experience, this introduction synthesizes key lessons that support or contradict the Causal Mechanism Claim. We find that both parts of the claim—increased policy relevance and strengthened causal capacity—are supported by the authors' experiences as bundled in this issue. However, we also identify challenges related to cross‐cutting issues such as communication and practical applicability and point to the importance of method integration. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of New Directions for Evaluation is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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