Identity and Conflict: Ties that Bind and Differences that Divide

Abstract

Conventional wisdom suggests that cultural differences make conflict more likely. Culture can unite and divide, but there exists little agreement among scholars over how identity forms among states, what distinctions are most salient, and when conflict is more likely. Researchers have tended to ‘confirm’ the role of identity in an ex post facto fashion, looking only at actual conflicts with cultural differences, without considering the opportunities for conflict among groups. We address a series of problems with existing conceptions of identity and ethnicity. We distinguish between shared and different culture by religion, language, and ethnicity. Rather than equating states with just the dominant groups, we also consider how relations involving secondary groups present in other states can give rise to conflict. We examine empirically the relationship between cultural similarities and differences and international dispute behavior in the post-World War II era. Our results suggest that culture and identity influence dispute patterns, but in ways that run counter to conventional beliefs. We find little evidence that conflict is more common between states where the dominant groups come from different cultural affiliations. If anything, our results suggest that violence is more likely among states with similar cultural ties, even when controlling for other determinants of conflict. Moreover, dyads where a group is politically privileged in one state but a minority in another tend to be particularly conflict prone. We conclude with suggestions for reorienting the study of identity and conflict in more constructive ways than the clash of civilization thesis.

Does discrimination breed grievances—and do grievances breed violence? New evidence from an analysis of religious minorities in developing countries

“…The clear majority of quantitative studies of religious conflict focus solely on religious identity, that is, where groups belonging to different religions are more violent or whether interreligious conflicts are more violent than intrareligious conflict, or they focus on religious diversity, that is, they create a single demographic variable to measure the extent of religious diversity in a state. Most of them find religious identity or diversity to influence the extent of conflict (De Soysa and Norda˚s, 2007;Ellingsen, 2005;Gartzke and Gleditsch, 2006;Olzak, 2011;Reynal-Querol, 2002;Rummel, 1997;Sambanis, 2001;Toft, 2007;Vanhanen, 1999), but there are some studies that disagree with this finding (Collier and Hoeffler, 2002;Fearon and Laitin, 2003;Lacina, 2006;Pearce, 2005;Sørli et al, 2005). A few go beyond this question to look at the religious content of conflict.…”

International Terrorism and the Clash of Civilizations

“…This is ironic given he also states that "a crucial test of a paradigm's validity and usefulness is the extent to which the predictions derived from it turn out to be more accurate than those from alternative paradigms" (Huntington 1996: 37). Consequently, critics have charged his work with being ambiguous, inconsistent and sometimes self-contradictory (Russett, Oneal and Cox 2000;Henderson and Tucker 2001;Gartzke and Gleditsch 2006). Due to space constraints, we cannot engage with these arguments in great detail.…”

Spatial Effects in Dyadic Data

“…Both monadic and undirected dyadic data offer only one option each for modeling contagion+ In contrast, there are five options for modeling spatial dependence if we analyze directed dyadic data+ The reason is that in directed dyads two actors i and j have an asymmetric interaction and one can distinguish dyads ij, where unit i is the source and unit j is the target, from dyads ji where these roles are reversed+ This means contagion can come from other dyads, as in undirected dyadic data, but contagion can also come from other sources or from other targets+ Moreover, where contagion stems from other sources or other targets, it can be their aggregate policy choices that matter or their choices with respect to only the specific dyad under consideration+ Starting with the option that directly resembles the modeling of spatial dependence in undirected dyadic data, dyad ij can be modeled to be more likely to sign a BIT if other dyads between capital-exporting and capital-importing countries 20+ Undirected dyad contagion can be further restricted such that all dyads containing either unit i or unit j are excluded from having a contagious effect+ Such exclusive undirected dyad contagion would be represented by y ij ϭ r (k i, m j v pq y km ϩ « ij + 21+ See Manger 2006;and Gartzke and Gleditsch 2006+ have already agreed on such a treaty+ This form of spatial dependence we call directed dyad contagion+ 22 Hence:…”