Applications of Complexity Theory in an English Metropolitan Police Force

Davies, Philip Andrew (2024). Applications of Complexity Theory in an English Metropolitan Police Force. PhD thesis The Open University.

DOI: https://doi.org/10.21954/ou.ro.00099284

Abstract

This research addresses the question “Can the methods of complexity theory be used in UK policing as an enabling tool for policy intervention, in providing evidence of possible consequences before policies are implemented?” A literature study shows complexity theory is without consensus on epistemology and application. Methodology is developed for exploring motivational consequences of policies on the workforce, involving building mathematical models using hypernetwork theory as the basis for computer simulation and a promising route to engage with practitioners. It is illustrated by the motivation of Police Community Support Officers (PCSOs) in the Neighbourhood Policing system of Greater Manchester Police. The computational model is based on qualitative data collected using Thematic Coding. This produced ‘behavioural codes’ defined as vertices. Six most prevalent were selected and combined into a hypersimplex:

Purpose (feedback)

Availability of supervision

Threat of harm

Relevance to role

Orientation to geographic responsibility

Lone working

The acronym <PATROL> facilitated design of the simulation. It also offers a conceptual model where combinations of vertices connect in given scenarios, supporting dialogue between policy maker and computer modeller and insights into simulated possible policy consequences on staff. This enables the policy maker to explore sufficient conditions for outcomes to be obtained that satisfied the policy objectives but not at the expense of staff motivation. Experiments established two concepts: combinatorial compensation and combinatorial tempering as adaptation of simulated policy conditions. The nature of hypernetworks introduce non-linearity into policy design, as multiple dimensions are being considered to achieve objectives, where combinations are not predictable from individual dimensions. A central tenet of the thesis is complexity science can be applied without computer programming skills, and ‘modelling’ can be done long before writing code. Following this there is an iterative interaction as the policy maker uses the program and requests the programmer for new or changed functionality. The method is proposed as a general framework for Agent-Based Modelling (ABM) of human systems.