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Criminal Sentencing by Preferred Numbers

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  • Mandeep K. Dhami
  • Ian K. Belton
  • Elizabeth Merrall
  • Andrew McGrath
  • Sheila M. Bird

Abstract

Criminal sentencing is a complex cognitive activity often performed by the unaided mind under suboptimal conditions. As such, sentencers may not behave according to policy, guidelines, or training. We analyzed the distribution of sentences meted out in one year in two different jurisdictions (i.e., England and Wales, and New South Wales, Australia). We reveal that sentencers prefer certain numbers when meting out sentence lengths (in custody and community service) and amounts (for fines/compensation). These “common doses” accounted for over 90 percent of sentences in each jurisdiction. The size of these doses increased as sentences became more severe, and doses followed a logarithmic pattern. Our findings are compatible with psychological research on preferred numbers and are reminiscent of Weber's and Fechner's laws. The findings run contrary to arguments against efforts to reduce judicial discretion, and potentially undermine the notion of individualized justice, as well as raise questions about the (cost) effectiveness of sentencing.

Suggested Citation

  • Mandeep K. Dhami & Ian K. Belton & Elizabeth Merrall & Andrew McGrath & Sheila M. Bird, 2020. "Criminal Sentencing by Preferred Numbers," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 17(1), pages 139-163, March.
    • Handle: RePEc:wly:empleg:v:17:y:2020:i:1:p:139-163
    DOI: 10.1111/jels.12246
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    References listed on IDEAS

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    1. Dorogovtsev, S.N. & Mendes, J.F.F. & Oliveira, J.G., 2006. "Frequency of occurrence of numbers in the World Wide Web," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 548-556.
    2. Aerts, Walter & Campenhout, Geert Van & Caneghem, Tom Van, 2008. "Clustering in dividends: Do managers rely on cognitive reference points?," Journal of Economic Psychology, Elsevier, vol. 29(3), pages 276-284, June.
    3. Harris, Lawrence, 1991. "Stock Price Clustering and Discreteness," The Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 389-415.
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    Cited by:

    1. Roger, Patrick & D’Hondt, Catherine & Plotkina, Daria & Hoffmann, Arvid, 2022. "Number 19: Another Victim of the COVID‐19 Pandemic?," LIDAM Reprints LFIN 2022012, Université catholique de Louvain, Louvain Finance (LFIN).
    2. Jakub Drapal & Michal Soltes, 2021. "Sentencing Decisions Around Quantity Thresholds: Theory and Experiment," CERGE-EI Working Papers wp715, The Center for Economic Research and Graduate Education - Economics Institute, Prague.

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