The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Between X and Y: how process tracing contributes to opening the black box of causality
Abstract
This article maps the methodological debate on process tracing and discusses the diverse variants of process tracing in order to highlight the commonalities beyond diversity and disagreements. Today most authors agree that process tracing is aimed at unpacking causal and temporal mechanisms. The article distinguishes two main types of use for process tracing. Some are more inductive, aimed at theory building (i.e. at uncovering and specifying causal mechanisms) while others are more deductive, aimed at theory testing (and refining). The paper summarizes the main added value and drawbacks of process tracing. It ends by providing ten guidelines for when and how to apply process tracing.
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Cites
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Cited by
Process Tracing and Historical Explanation
Mahoney, J. (2015) · Security Studies · doi:10.1080/09636412.2015.1036610 · Cited by 296
An Introduction to Polycentricity and Governance
Stephan, M., Marshall, G., & McGinnis, M. (2019) · Governing Complexity · doi:10.1017/9781108325721.002 · Cited by 112
Thiel, A., & Moser, C. (2019) · Governing Complexity · doi:10.1017/9781108325721.004 · Cited by 58
Mitigating risk of failure in information technology projects: Causes and mechanisms
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Mechanisms, Bayesianism, and process tracing
Mahoney, J. (2016) · New Political Economy · doi:10.1080/13563467.2016.1201803 · Cited by 26
Metadata
- Authors
- Trampusch, C., & Palier, B.
- Venue
- New Political Economy
- Publisher
- Informa UK Limited
- Published
- 2016-02-22
- Volume
- 21
- Issue
- 5
- Pages
- 437-454
- ISSN
- 1356-3467 (ISSN-L)
- 1469-9923
- OpenAlex
- W2290955396
- Cited by
- 328
- References
- 52
- FWCI
- 77.17
- Type
- journal article
- Language
- en
- Update notices
- correction (2016-04-29)
- Open access
- closed
- Funders
- Agence Nationale de la Recherche (ANR-11-LABX-0091, ANR-11-IDEX-0005-02)
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.