Formalised modelling of action theory in the explanation of crime for prediction, deduction and intervention

This dissertation proposes an original approach to theory of action in psychological and sociological criminology, i.e. to theory explaining the causation of human wilful behaviour at great abstraction through the information processing conducted by each individual human agent. It is argued that the model presented in this dissertation, the so-called Minimal Model of Action, is more theoretically comprehensive than prior familiar approaches originating in various related fields, in particular through its integration of both rational and habitual aspects of behaviour in a unified causal argument. Secondly, it is argued that the model is more methodologically appealing than previous approaches due to its formalisation through conventional mathematics. The proposed model is brought to bear on more concrete behavioural data and criminological problems in three separate chapters so as to scrutinise its validity and tractability from three methodologically different angles. An experimental chapter shows that empirical responses to computer-based scenario tasks frequently display behaviour patterns, especially forms of habituation, which the Minimal Model of Action in its simulated implementations and unlike previous models manages to explain and predict. In the following chapter, it is mainly shown through mathematical deduction both in continuation of and in juxtaposition to prior economic reasoning in which ways “optimum law enforcement” levels are systematically overestimated (and sometimes underestimated) under a variety of conditions when over-rationalised conceptions of the individual offender are employed. Finally, a chapter on aggregate levels of small-scale public corruption employs the general model to simulate a typical criminal phenomenon to the explanation of which economic and broader social conceptions of human agency equally should contribute.EThOS - Electronic Theses Online ServiceGBUnited Kingdo