Crime and punishment as a social system: the case of prison overcrowding

Abstract

Purpose This paper presents an actor-based conceptualization of the increasing oscillatory pattern of prison overcrowding in Colombia. The research proposes a dynamic hypothesis that explains that unintended behavioural pattern as a result of delayed balance feedback loops shaped by decision-making processes of actors that intend to control crime. This system matches a well-known systemic archetype that explains those persistent oscillations. The paper also introduces a simulation model for testing that dynamic hypothesis and for delivering concrete courses of action. This work illustrates the relevance for policymakers to understand the dynamic complexity of social systems as the outcome of the agency of actors who take action to defend their own interests. Such actions ultimately form a complex web of interactions that drive the performance of such systems with unintended consequences. In particular, the construction of explicit models provides better chances of devising policies that consider the system-level implications of those interactions. Design/methodology/approach This work uses system dynamics modelling. First, the paper presents a conceptual model anchored in operational thinking, which refers to the identification of actors and decisions, and the manner in which those decisions ultimately build the respective social system in which the oscillatory pattern emerges. Second, it identifies key feedback structures that result from those chains of decisions. Finally, the paper introduces a simulation model for suggesting policy implications for decisionmakers. Findings The increasing oscillatory pattern that prison overcrowding in Colombia has displayed over the last 20 years is the outcome of a wide variety of laws that increase sanctions on criminal conducts, a phenomenon known as “legislative inflation”. Such reactions against crime are propelled and sustained by society and policymakers as the result of static and linear thinking that simply delivers “more punishment” of crime – harsher legislation and longer prison terms – which ultimately boosts long-term prison overcrowding and further cycles of crime control and overcrowding. Such actions create permanent negative feedback loops that involve various material and information delays, which – coupled with the reinforcing feedback loops – explain the previously mentioned behavioural pattern. Through a system dynamics simulation model, this paper tests and explains the proposed dynamic hypothesis and shows how policymakers can enhance and develop their dynamic understanding to explore and design effective policies intended to tackle prison overcrowding. Practical implications This paper presents a practical and concrete case that bridges the fields of criminal policy and prison management through systems thinking. It uses the case of prison overcrowding in Colombia to demonstrate the relevance of incorporating systemic thinking into the cognitive portfolio of policymakers if they aspire to improve complex systems. Originality/value Criminal policy and prison management are different fields that typically belong to different traditions (law and criminal psychology for the former, public administration for the latter). The work presented here bridges those perspectives under a single engineering and systemic perspective that answers questions in both fields and serves as a unifying framework for designing more coherent criminal policies that meet the practical requirements and restrictions that prison management implies.

Handling the Subjacent Complexity of a Resocialization Program for Inmates: A Systemic Analysis and Leverage Points

“…The underlying dynamic complexity can be thought of as the outcome of choices made by social actors defending their interests that eventually lead to ultimate, unintended, or unexpected consequences. Uncovering the underlying structures that shape the systemic behavioral pattern [16] can help to find leverage points to tackle those consequences [17], as well as specific objectives that are valid in unique contexts [18].…”