Applied social simulation for public policy

LEONARDO G. RODRÍGUEZ ZOYA

San Luis Potosí

Simposio; Primer Simposio Virtual de Sociología Computacional; 2020

Iberoamerican Network of Computational Sociology

INTRODUCTION: SocLab is a theoretical, methodological and computer ?framework for the modeling, the simulation and the analysis of power relationships in social organizations, and more generally in systems of organized action? (Sibertin-Blanc et al., 2013: 1). We propose to use SocLab to tackle a relevant problem of public policy analysis: the question of social feasibility of a policy. The theoretical speech gives equal importance to the social, economic, technical and environmental dimension of a policy. However, ?in practice, little attention is paid to the social dimension: the other dimensions [?] are considered with much more attention? (Adreit et al., 2009: 2).OBJECTIVE: The goal of this paper is to analyze the social feasibility of a concrete experience of public policy using SocLab framework. The case of study is a cluster of fine fruit producers in Patagonia, Argentina. By doing so, we show how and why social simulation in general and, SocLab in particular, may help policymakers to analyze social feasibility of public policies.METHODOLOGY: SocLab is an agent-based social simulation model grounded on the Sociology of Organized Action (SOA) developed by Michel Crozier and Erhard Friedberg (Crozier and Friedberg 2010). SocLab framework allows to: model different types of organizations (formal and informal), analyze their structure, and simulate their behavior and interactions among the agents that constitute them. It´s main goal is to study the organizational dynamics and the forms of regulation of social systems. SocLab?s methodology can be sum up in nine steps: (1) identify actors, (2) identify resources, (3) identify relations, (4) actor-relations matrix, (5) actor?s stakes on the relations he depends, (6) behavioral space constraints, (7) definition of a qualitative scale for the state of the relation, (8) model effect functions, (9) define solidarities. All this methodological decisions can be conducted through an intuitive interface without having computer programing skills. RESULTS: First we explain how we have used qualitative data of fine fruit cluster to develop in SocLab a computer model empirically grounded following the nine step methodology previously presented. Second we summarize the model integrated by five actors and eight resources. Finally, we focus our analysis on two SocLab indexes: power and action capacity. The latter express the degree an actor can access the resources he needs to achieve his goals. Power measures the amount of action capacity one actor grants to others. CONCLUSION: A SocLab model can be defined as a social game integrated by actors (players) and their relations. Structural analysis helps us to understand the possibilities and limits of the game. Simulation analysis allows us to obtain a dynamic representation of the game. SocLab calculates power and action capacity indexes in both structural and simulation analysis. Our structural analysis reveals a deep conflict between two kinds of producers: handmade and industrial producers. Social simulation reveals an outstanding and counter intuitive finding: industrial producers have two times the level of power of handmade producers (29 vs 15 points); however, the industrials are by far the most unsatisfied actor of the system. This allow us to rise question about the feasibly of the cluster. We explore how applied social simulation could support the decision making process of public policy.Adreit, F., et al., (2009). Using Soclab for a Rigorous Assessment of the Social Feasibility of Agricultural Policies. International Journal of Agricultural and Environmental Information Systems, 2(2), 1-15. Crozier, M., & Friedberg, E. (2010). L'acteur et le système. Paris: Seuil.Sibertin-Blanc, C., et al., (2013). SocLab: A Framework for the Modeling, Simulation and Analysis of Power in Social Organizations. Journal of Artificial Societies and Social Simulation, 16(4), 1-30.