Version 1.0

Replication Data for: Making Trains from Boxcars: Studying Conflict and Conflict Management Interdependencies

Owsiak, Andrew;Greig, J. Michael;Diehl, Paul

Description

Research on international conflict management remains largely siloed,with studies omitting conflict events and focusing on disparate conflictmanagement strategies (e.g., mediation, or peacekeeping); yet we knowthat strategies regularly interact with conflict events and one another(e.g., within the same conflict). If one imagines conflict events andconflict management strategies as train boxcars, and begins from theobservation that boxcars travel in trains (i.e., collections of boxcarslinked together in a purposefully constructed, meaningful way), a keyquestion emerges: how do we build trains from conflict managementstrategy boxcars? How do we move from the impulse to isolate thesestrategies artificially and study them discretely, to theorizing about andexamining the interdependence between them directly. The contributorsto this special issue address that broad question. In this introductoryarticle, we first explain the challenge at hand, outline the forms conflictmanagement interdependence can theoretically take, and define theconflict management strategies that feature throughout the issue. Wethen conduct a multidimensional scaling exercise to ascertain the mostpromising dimensions along which to theorize conflict managementinterdependence. This analysis shows that the myriad conflictmanagement strategies organize along two prominent dimensions:whether the strategy pursues a more integrative or distributive outcome,and how costly the strategy is for its user to employ. The analysis, farfrom being the last word, serves as an opening salvo for further researchon conflict management interdependence. Finally, we discuss the various articles in this special issue, highlighting their contributions and tyingthem together into a few main themes.

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Metrics

Dataset Index

0.1

FAIR Score

15%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Harvard Dataverse

License

Creative Commons Zero v1.0 Universal

Assigned Domain

Subfield

Sociology and Political Science

Field

Social Sciences

Domain

Social Sciences

Confidence Score

51%

Source

Open Alex

Keywords

Social Sciences

Normalization Factors

FT

51.92

CTw

1.00

MTw

1.00