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The evolution of norms within a society of captives

Journal of Economic Interaction and Coordination volume 16, pages 529–556 (2021)Cite this article

Abstract

How do norms evolve when people have no choice to opt out of social interactions? One example of such a setting is prison. Past research usually relies on ethnographic work to understand the emergence and maintenance of norms among prisoners. We instead use this rich qualitative literature to inform an agent-based model to demonstrate how norms evolve in response to demographic changes in prison. In the model, agents play a one-shot, though possibly repeated, prisoner’s dilemma with other agents. Agents lack the ability to decline to play with their selected opponent. We consider tag-mediated play and norm enforcement as mechanisms to facilitate prisoner cooperation and to examine the effects of increasing prison populations and increasing ethnic heterogeneity on the maintenance of cooperative norms. We also calibrate the model with empirical data from the California prison system. Parameters of the model correspond to demographic changes between 1951 and 2016, where the size of the prison population increased 14-fold and ethnic heterogeneity by 30%. Simulation results show that such changes dramatically decrease levels of cooperation and compliance. These results are consistent with the actual observed breakdown of the cooperative norms in California prisons.

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Notes

  1. It is notoriously difficult to perform any human subject experimentation in this area. See, for example, the Stanford Prison Experiment, described in Haney et al. (1972).

  2. De Marchi and Page (2014) provides an excellent recent survey of the use of agent-based models in studying political and social questions.

  3. This paper also contributes to the literature that applies modeling and simulation to criminal justice issues. A seminal paper in this literature is Joshua Epstein’s (2002) model of civil violence. Goh et al. (2006) and Zou et al. (2012) provide refinements to that model. See also Melleson et al. (2012) on burglary, Austin et al. (2012) on street gang affiliation, and Tako and Robinson (2010) on modeling the U.K. prison population.

  4. Leeson (2007a, b) and Murtazashvili and Murtazashvili (2015) emphasize that it is often too costly to rely on government to enforce rights. There is also a large literature examining the conditions under which anarchy delivers desirable social and economic outcomes (Powell and Stringham 2009; Mildenberger 2015; Luther 2015).

  5. See Prietula and Conway (2009), Kendal et al. (2006), and Mahmoud et al. (2012) for other examples of Axelrod-inspired models of meta-norm emergence. See Horne (2001), Bendor and Mookherjee (1990), Sampson et al. (1997), Carpenter and Matthews (2010), and Fehr and Fishbacher (2004) for discussion of theoretical and experimental examples of third-party norm enforcement. See Kusakawa et al. (2012) for an example of an experiment in which the presence of a witness helps to encourage cooperative behavior in a one-shot PD.

  6. We define “doing better” as #utils current generation > #utils previous generation * tolerance. The greater the tolerance factor, the more certain the agent is that the new strategy is better. The tolerance factor helps to encourage stability on the margin, so the agent doesn’t cycle endlessly over a set of nearly optimal strategies.

  7. The strategies are shown in Table 2 on page 10. Since we assume agents are not hypocrites, this means that new agents are actually more likely to be cooperative, since there are relatively more cooperative strategies.

  8. The treatments are the same as those described on page 17, above.

  9. See Law and Kelton (2000) for more on regression analysis of simulation models.

  10. The California Department and Corrections classifies non-white, non-black, and non-Hispanic prisoners into the category “other.”

  11. The qualitative results from this section are similar if this parameter is set to zero.

  12. See Law and Kelton (2000: pp 582–584) for more information on the use of common random numbers as a variance reduction technique.

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Authors and Affiliations

  1. Graduate School of Defense Management, Naval Postgraduate School, Monterey, CA, USA

    Chad W. Seagren

  2. Department of Political Science and the Political Theory Project, Brown University, Providence, RI, USA

    David Skarbek

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  1. Chad W. Seagren
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  2. David Skarbek
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Correspondence to Chad W. Seagren.

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Seagren, C.W., Skarbek, D. The evolution of norms within a society of captives. J Econ Interact Coord 16, 529–556 (2021). https://doi.org/10.1007/s11403-021-00316-7

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Keywords

  • Self-governance
  • Norms
  • Prison
  • Agent-based model

JEL Classification

  • K4
  • P48
  • P37