Academic journal article Public Administration Quarterly

A Complexity Science View of Modern Police Administration

Academic journal article Public Administration Quarterly

A Complexity Science View of Modern Police Administration

Article excerpt


Police agencies are bureaucratic paramilitary organizations that have traditionally been slow to change. In recent years, the arrival of the community policing philosophy has induced drastic attempts of organizational change in police organizations by mandating a decentralized policing style wherein police agencies must de-specialize and officers must have closer integration with the communities they serve. This paper argues that the attempted organizational changes have been largely unsuccessful due to administrators failing to understand that they operate in complex adaptive systems in which linear models of change are unsuccessful. This article offers a plausible explanation for this failure in organizational change by deviating from traditional paradigms of organizational theory and change and using the concepts of attractors and self-organization derived from the complexity sciences as its framework. This is accomplished by first providing the reader with a brief background on complexity science and its applications to organizations. The next section introduces the reader to the character of the police organizations and their complex nature. Finally, the paper applies complexity science to community policing, illustrating that police organizations are public entities that operate in an environment that is far too complex to apply linear models of change.

Complexity science offers a new paradigm to understand the complexities of community policing and its environment. In his now classic work on scientific revolutions, Kuhn (1996) describes the evolution of scientific inquiry in which paradigms gradually shift. In Kuhn's paradigms, researchers and scientists come to accept basic assumptions and methods to inquire their subject matters. The prevailing paradigm receives the label of "normal science." During the period in which a normal science prevails, scientists engage in research that meets the criteria of the paradigm, which Kuhn describes as puzzle solving within the confines of the paradigm. In Kuhn's words, a paradigm "attempt[s] to force nature into the performed and relatively inflexible box that the paradigm supplies" (p. 24). Phenomena that will not fit in this paradigmatic box are ignored and not seen at all. After a while, these unfitting phenomena lead some scientists to break away from the normal science and form a new paradigm. Complexity science is such a new paradigm.

Arguably, the theory and study of organizations has been entrenched in the normal science of our times (Daft & Lewin, 1997). The current explanations of police organizations are examples of the entrenchment in a normal science. Public administration and policy researchers also operate within the confines of today's normal science. Modern social scientists in general attempt to force fit data into the linear thinking of the prevailing paradigm. Social science textbooks acknowledge the existence of outliers, data that deviates from the normal distribution, and nonlinear relationships, but they recommend to exclude them from analyses or mathematically transform non-normal and non-linear data to fit them into linear models. By over-fitting data to linear models, researchers are fundamentally changing the true nature of relationships and arriving at results that are approximations of social phenomena at best. Researchers must ask whether the prevailing linear thinking really provides an adequate explanation of the changes in and structures of modern organizations. The theory and application of complexity science can greatly aid researchers in understanding organizations.


Linear thinking and models are part of the traditional scientific method's reductionist paradigm, which encompasses notions of order, predictability, and determinism. Reductionists subscribe to the practice of breaking down structural components to establish clear cause and effect relationships. …

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