Abstract
Computer simulation models have changed the ways in which researchers are able to observe and study social phenomena such as crime. The ability of researchers to replicate the work of others is fundamental to a cumulative science, yet this rarely occurs in computer simulations. In this paper, we argue that, for computer simulations to be seen as a legitimate methodology in social science, and for new knowledge to be generated, serious consideration needs to be given to how simulations could or should be replicated. We develop the concept of systematic replication, a method for developing simulation experiments that move towards a generalisable inference that is directed, explicit, and incorporates complexity incrementally. Finally, we outline how the discrete parts of this process might be carried out in practice, using a simple simulation model.
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Notes
For the purposes of this article, we define a simulation model as a system defined by rules, some of which relate to interactions between components of the system. Allowing the system to ‘run’ the application of these rules generates output. All aspects of the system are defined and directly programmed by the researcher.
These comments apply equally to any discipline that acts as a ‘service’ discipline to others. Obvious examples include applied statistics and mathematics. We do not believe all, or even most, computer scientists (or statisticians and mathematicians) are rapacious mercenaries obsessed with methodological gymnastics for the sake of it.
Computer scientists use convergence and sensitivity tests at this stage as well. Our focus in this article is primarily on the social scientists who we feel have the most to gain from testing the validity of models that focus on social phenomena.
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Ibid
For reasons similar to those of Shadish et al. (2002), we represent Cronbach’s notation in a modified form, which we believe makes it more interpretable.
This list is by no means exhaustive and serves only to aid the presentation of the case studies.
Later simulations may also recreate treatments such as crime prevention interventions in a more analogous way to traditional uses of Treatment within utos. Importantly though, such intervention simulation relies heavily upon a sufficiently validated and verified base model of all the interactions associated with crime and its key elements. Therefore, the initial models we describe only strive towards theoretically, rather than operationally, relevant applications.
Of course, in reality, there were other differences between the two studies, so it is unlikely that purely setting differences were responsible for the difference.
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Acknowledgements
A version of this paper was presented at a meeting of the Crime Simulation Network and feedback from numerous delegates has improved the paper. The authors would also like to thank the three anonymous reviewers for their constructive comments that have improved the scope of the arguments set out in the paper.
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Townsley, M., Birks, D.J. Building better crime simulations: systematic replication and the introduction of incremental complexity. J Exp Criminol 4, 309–333 (2008). https://doi.org/10.1007/s11292-008-9054-4
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DOI: https://doi.org/10.1007/s11292-008-9054-4