Understanding Civil War Violence through Military Intelligence

Douglass, Rex W.

doi:10.1093/acprof:oso/9780199378296.003.0023

Cited by 5 publications

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“…Further, the types of information gathered in records and reports may shift over time and space as combatants respond to conflict. For example, Douglass (2016) demonstrates how missingness in the attributes collected by US Army Intelligence during the Vietnam War varied systematically across both the type of operation and the demographics of potential targets. There may also be incentives to report acts of government violence differently from rebel violence.…”

Section: Advantages and Limitations Of Data From Conflict Archivesmentioning

confidence: 99%

“…Researchers should use this information to develop testable propositions about what is and is not contained in the archives, which can then be used to confirm or invalidate theories of the data generating process (e.g. Douglass, 2016;Guberek & Hedstrom, 2017;Douglass & Harkness, 2018). These tests should be made explicit, and the results should be preserved for subsequent replication by later researchers.…”

Section: Best Practices For Generating and Analyzing Data From Conflimentioning

confidence: 99%

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New findings from conflict archives

Balcells

Sullivan

2018

Journal of Peace Research

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As they pursue information and deploy violence during conflict, combatants compose, catalog, and preserve a wide variety of records, such as memos, investigative reports, and communiqués. In an increasing number of post-conflict scenarios, these records are being archived and released publicly, quickly becoming a critical new source of data for studies of peace and conflict. The objective of this special issue is to advance a new research agenda focused on the systematic analysis of conflict archives. The contributors each spent significant time collecting original data from often-dusty archives and, in many cases, developed new methodologies for sampling, cataloging, and analyzing historical documents. Their findings reveal how violence simultaneously shapes and is shaped by factors that remain largely unobservable using more conventional sources of conflict data, including clandestine mobilization, bureaucratic accountability, and political identities. By considering these studies in relation to one another, this introduction aims to provide readers with a comprehensive understanding of field research strategies and analytical techniques for studying original data from conflict archives. We conclude that while archival data are subject to their own biases that must be considered, this research agenda addresses significant limitations associated with traditional data sources and, in turn, pushes scholars to rethink many of the mechanisms underlying the causes and dynamics of peace and conflict.

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Section: Advantages and Limitations Of Data From Conflict Archivesmentioning

confidence: 99%

Section: Best Practices For Generating and Analyzing Data From Conflimentioning

confidence: 99%

New findings from conflict archives

Balcells

Sullivan

2018

Journal of Peace Research

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“…We do not suggest that researchers adopt a single method, or even a particular class of methods in this paper; we simply wish to emphasize that researchers are likely selling their theories short in terms of predictive power by using overly restrictive models that are underdetermined by theory. We note that, though most examples are relatively new, the call for more focus on predictive checking is not new to applied political science research (see e.g., Beck, King and Zeng 2000; Ward, Greenhill and Bakke 2010; Beger, Dorff and Ward 2014; Hill and Jones 2014; Schnakenberg and Fariss 2014; Chenoweth and Ulfelder 2015; Douglass 2015; Graham, Gartzke and Fariss 2015). Given the importance of predictive checking, and the recent discussion of transparency and the replication standard—we view exact replication as specifically a form of model validation—it is an important point to re-emphasize here: regularization 21 can be used to decrease threats to predictive validity from over/underfitting an empirical model by focusing on the minimization of generalization error 22 .…”

Section: Empirical Validation Of Unspecified Functional Forms and Modmentioning

confidence: 99%

Enhancing Validity in Observational Settings When Replication is Not Possible

Fariss¹,

Jones²

2017

PSRM

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We argue that political sciexntists can provide additional evidence for the predictive validity of observational and quasi-experimental research designs by minimizing the expected prediction error or generalization error of their empirical models. For observational and quasi-experimental data not generated by a stochastic mechanism under the researcher’s control, the reproduction of statistical analyses is possible but replication of the data-generating procedures is not. Estimating the generalization error of a model for this type of data and then adjusting the model to minimize this estimate—regularization—provides evidence for the predictive validity of the study by decreasing the risk of overfitting. Estimating generalization error also allows for model comparisons that highlight underfitting: when a model generalizes poorly due to missing systematic features of the data-generating process. Thus, minimizing generalization error provides a principled method for modeling relationships between variables that are measured but whose relationships with the outcome(s) are left unspecified by a deductively valid theory. Overall, the minimization of generalization error is important because it quantifies the expected reliability of predictions in a way that is similar to external validity, consequently increasing the validity of the study’s conclusions.

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Conflict and Peace Economics: Retrospective and Prospective Reflections on Concepts, Theories, and Data

Bräuer

Anderton

2020

Defence and Peace Economics

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Understanding Civil War Violence through Military Intelligence

Cited by 5 publications

References 0 publications

New findings from conflict archives

New findings from conflict archives

Enhancing Validity in Observational Settings When Replication is Not Possible

Conflict and Peace Economics: Retrospective and Prospective Reflections on Concepts, Theories, and Data

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