Do Peaceful Social Systems Exist? Do They Exist in Societies that do not Engage in War?

 
 
 
 

Research Title: Societies within peace systems avoid war and build positive intergroup relationships

Research Authors: Douglas P. Fry, Geneviève Souillac, Larry Liebovitch, Peter T. Coleman, Kane Agan, Elliot Nicholson-Cox, Dani Mason, Frank Palma Gomez & Susie Strauss

Research Publisher: Humanities & Social Sciences Communications

Research Publication date: January 2021

What does research tell us about social systems within war-torn contexts?

In a recent report “Societies within peace systems avoid war and build positive intergroup relationships,” researchers identified 16 peace systems through anthropological and historical literature and used correlation analyses and machine learning algorithms (Random Forest) to compare these peace systems to 30 non-peace systems with respect to key attributes that are hypothesized to contribute to intergroup peace. A total of 12 attributes were used for this study (8 peace-related and 4 war-related).

Overall, the study found the selected attributes hypothesized for promoting intergroup peace were more developed in peace systems than elsewhere. Of all the 12 attributes tested, overarching common identity; positive social interconnectedness; interdependence; non-warring values and norms; non-warring myths, rituals, and symbols; and peace leadership, had the most significant results. The machine learning algorithm also found non-warring myths, rituals, and symbols to have the highest relative importance for a peace system outcome.

Check out some of the interesting approaches used by the study:

  • Anthropological and historical literature was used to identify clusters of neighboring societies that do not make war with each other, i.e. peace systems.

  • The Standard Cross-Cultural Sample (SCCS), a database of 186 cultural provinces from around the world and various types of societies, was used to ensure a geographically representative sample was selected for this study.

  • A supervised machine learning algorithm called Random Forest was used to assess the relative importance of the attributes selected when classifying the attributes between peace systems and non-peace systems.

AfP Blog Author: Shaziya DeYoung, Senior Associate - Learning & Evaluation

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