Policy and Complex Systems
Social Conflict Scenarios
Social conflict ( Rubin , Pruitt , & Kim ,
1994 ) occurs among large groups of people who differ on specific issues that each group holds important , with interests driven by differing values and identities . It can be latent but frequently bursts in the open around joint decisions . At such decision points , conflicting social groups contend with each other . Conflicts around politics and consequential policies at the federal , state , and local levels fall in this category , as do international disputes . The waging of conflict can be pursued peacefully through processes such as voting or negotiations ; at times , it can also descend into violence , both within and between countries . The peaceful decision processes are by no means necessarily friendly . For example , members of the clashing groups can actively engage in persuading each other to their point of view in order to secure favorable outcomes .
Conflicts tend to be very different from each other despite some general similarities . For example , although environmental conflicts usually revolve around environmental issues , their location , time , political and social contexts , specific issues , and participants make them both complex and rather unique . At the eye level of group members , interveners or observer , patterns and future directions are rather resistant to prediction and may appear chaotic . It is also difficult to foresee the outcomes resulting from the numerous decisions of interacting parties in time . The chaotic appearance at one observation level may look different at a higher level . At such a level , we may no longer discern the detailed interactions but , as with other with other complex phenomena , we may distinguish patterns . Then it is possible to derive a range of possible social conflict trajectories , or scenarios .
When two groups are engaged in conflict , the web of interactions inside each group and between the groups can be represented as two interconnected networks . Inside each network and between them , the groups ’ members are nodes and the inter-node links are their interactions . This approach , used in physics to study complex phenomena , is applied here to the study of complex social interactions . The utility of applying the network modeling approach to the study of social conflicts and generation of scenarios resides in the following notion : stakeholders to social conflicts need to foresee the unpredictable ( Bonabeau , 2002 ; Lempert , Popper , & Bankes , 2002 ).
To engage in a joint decision — where the outcome for all depends on the choices of many — conflicting parties need to prepare strategies contingent on their opponents ’ reactions . However , in complex situations with numerous individuals making interacting choices , such reactions are difficult to predict reliably enough to prepare responses . Therefore , it may be wiser for each party to abandon the quest for prediction and switch to anticipation . Instead of aiming to figure out what the opponent will do ( equivalent to a point prediction ), it is more feasible and helpful to anticipate a range of possible opponent reactions and prepare for that range instead of the point estimate ( Lempert et al ., 2002 ).
Underlying the anticipation approach is the idea that social conflicts occur within complex , interrelated physical and social systems . Decisions in such contexts are fraught with uncertainty . Unlike simple onecause – one-effect relationships that can be understood and managed , social systems may yield some of the results sought , but often also a host of unforeseen and negative side effects . To compound the difficulty , some decision consequences accrue quickly while others take longer time to show
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