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I develop a model of how states process this information and examine how this learning affects international conflict. The model builds off of cognitive balance theory and foreign policy learning models, and breaks new ground in its ability to provide a contextual assessment of reputation in world politics. I then investigate whether a dyad is more likely to experience conflict if at least one of the states has a reputation for hostility. This hypothesis is tested empirically across all dyads in the international system from 1817-2000. The results indicate that states do engage in this learning behavior, and that the information generated by extra-dyadic interaction of states has a significant bearing upon the likelihood of dyadic conflict."}}]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"reputation conflict international relations"}}]},{"typeName":"topicClassification","multiple":true,"typeClass":"compound","value":[{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"political science international conflict processes"}}]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Crescenzi, Mark J.C. \"Reputation and Interstate Conflict\", American Journal of Political Science 2007"}}]},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2011-11-02"}]}},"files":[{"description":"data used for empirical analysis in the paper","label":"ajps_rr_2.tab","restricted":false,"version":1,"datasetVersionId":43746,"categories":["replication data"],"dataFile":{"id":2321409,"persistentId":"doi:10.7910/DVN/UMQC2D/NHABCB","pidURL":"https://doi.org/10.7910/DVN/UMQC2D/NHABCB","filename":"ajps_rr_2.tab","contentType":"text/tab-separated-values","friendlyType":"Tab-Delimited","filesize":222046527,"description":"data used for empirical analysis in the paper","categories":["replication data"],"storageIdentifier":"s3://dvn-cloud:74685","originalFileFormat":"application/x-stata","originalFormatLabel":"Stata Binary","originalFileSize":127103809,"originalFileName":"ajps_rr_2.dta","UNF":"UNF:5:trQaWReMA0jZnDiVxpos7Q==","rootDataFileId":-1,"md5":"68a638fcb5d9f4fd8dad4f512b285d8e","checksum":{"type":"MD5","value":"68a638fcb5d9f4fd8dad4f512b285d8e"},"tabularData":true,"creationDate":"2011-11-02","publicationDate":"2011-11-01","lastUpdateTime":"2011-11-02T14:10:44Z","fileAccessRequest":false}},{"description":"do files (stata) for the cox models in the article","label":"cox models_ajpsrr.do","restricted":false,"version":1,"datasetVersionId":43746,"dataFile":{"id":2321411,"persistentId":"doi:10.7910/DVN/UMQC2D/CNMIV6","pidURL":"https://doi.org/10.7910/DVN/UMQC2D/CNMIV6","filename":"cox models_ajpsrr.do","contentType":"text/x-stata-syntax; charset=US-ASCII","friendlyType":"Stata Syntax","filesize":291,"description":"do files (stata) for the cox models in the article","storageIdentifier":"s3://dvn-cloud:74687","rootDataFileId":-1,"md5":"4dcfc8cce0be55981709ad756a67b33e","checksum":{"type":"MD5","value":"4dcfc8cce0be55981709ad756a67b33e"},"tabularData":false,"creationDate":"2011-11-02","publicationDate":"2011-11-01","lastUpdateTime":"2011-11-02T14:10:44Z","fileAccessRequest":false}}]}}}