IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/2009-36-3.html
   My bibliography  Save this article

Co-Operative Punishment Cements Social Cohesion

Author

Listed:

Abstract

Most current attempts to explain the evolution - through individual selection - of pro-social behavior (i.e. behavior that favors the group) that allows for cohesive societies among non related individuals, focus on altruistic punishment as its evolutionary driving force. The main theoretical problem facing this line of research is that in the exercise of altruistic punishment the benefits of punishment are enjoyed collectively while its costs are borne individually. We propose that social cohesion might be achieved by a form of punishment, widely practiced among humans and animals forming bands and engaging in mob beatings, which we call co-operative punishment. This kind of punishment is contingent upon - not independent from - the concurrent participation of other actors. Its costs can be divided among group members in the same way as its benefits are, and it will be favoured by evolution as long as the benefits exceed the costs. We show with computer simulations that co-operative punishment is an evolutionary stable strategy that performs better in evolutionary terms than non-cooperative punishment, and demonstrate the evolvability and sustainability of pro-social behavior in an environment where not necessarily all individuals participate in co-operative punishment. Co-operative punishment together with pro-social behavior produces a self reinforcing system that allows the emergence of a 'Darwinian Leviathan' that strengthens social institutions.

Suggested Citation

  • Klaus Jaffe & Luis Zaballa, 2010. "Co-Operative Punishment Cements Social Cohesion," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(3), pages 1-4.
  • Handle: RePEc:jas:jasssj:2009-36-3
    as

    Download full text from publisher

    File URL: https://www.jasss.org/13/3/4/4.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Martin A. Nowak & Karl Sigmund, 1998. "Evolution of indirect reciprocity by image scoring," Nature, Nature, vol. 393(6685), pages 573-577, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mike Farjam & Marco Faillo & Ida Sprinkhuizen-Kuyper & Pim Haselager, 2015. "Punishment Mechanisms and Their Effect on Cooperation: A Simulation Study," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(1), pages 1-5.
    2. Niu, He & Chen, Yuyou & Ye, Hang & Zhang, Hong & Li, Yan & Chen, Shu, 2020. "Distinguishing punishing costly signals from nonpunishing costly signals can facilitate the emergence of altruistic punishment," Applied Mathematics and Computation, Elsevier, vol. 371(C).
    3. Klaus Jaffe, 2015. "Agent based simulations visualize Adam Smith's invisible hand by solving Friedrich Hayek's Economic Calculus," Papers 1509.04264, arXiv.org, revised Nov 2015.
    4. Roos, Patrick & Gelfand, Michele & Nau, Dana & Lun, Janetta, 2015. "Societal threat and cultural variation in the strength of social norms: An evolutionary basis," Organizational Behavior and Human Decision Processes, Elsevier, vol. 129(C), pages 14-23.
    5. Klaus Jaffe, 2014. "Visualizing the Invisible Hand of Markets: Simulating complex dynamic economic interactions," Papers 1412.6924, arXiv.org, revised Apr 2015.
    6. Hang Ye & Fei Tan & Mei Ding & Yongmin Jia & Yefeng Chen, 2011. "Sympathy and Punishment: Evolution of Cooperation in Public Goods Game," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(4), pages 1-20.
    7. Gabriela Koľveková & Manuela Raisová & Martin Zoričak & Vladimír Gazda, 2021. "Endogenous Shared Punishment Model in Threshold Public Goods Games," Computational Economics, Springer;Society for Computational Economics, vol. 58(1), pages 57-81, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carattini, Stefano & Gillingham, Kenneth & Meng, Xiangyu & Yoeli, Erez, 2024. "Peer-to-peer solar and social rewards: Evidence from a field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 219(C), pages 340-370.
    2. Wang, Xiaofeng & Chen, Xiaojie & Gao, Jia & Wang, Long, 2013. "Reputation-based mutual selection rule promotes cooperation in spatial threshold public goods games," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 181-187.
    3. Wang, Chengjiang & Wang, Li & Wang, Juan & Sun, Shiwen & Xia, Chengyi, 2017. "Inferring the reputation enhances the cooperation in the public goods game on interdependent lattices," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 18-29.
    4. Frauke von Bieberstein & Andrea Essl & Kathrin Friedrich, 2021. "Empathy: A clue for prosocialty and driver of indirect reciprocity," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-15, August.
    5. Matthias Greiff & Fabian Paetzel, 2012. "The Importance of Knowing Your Own Reputation," MAGKS Papers on Economics 201236, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Charness, Gary & Du, Ninghua & Yang, Chun-Lei, 2011. "Trust and trustworthiness reputations in an investment game," Games and Economic Behavior, Elsevier, vol. 72(2), pages 361-375, June.
    7. Cubitt, Robin P. & Drouvelis, Michalis & Gächter, Simon & Kabalin, Ruslan, 2011. "Moral judgments in social dilemmas: How bad is free riding?," Journal of Public Economics, Elsevier, vol. 95(3), pages 253-264.
    8. Deng, Zhenghong & Wang, Shengnan & Gu, Zhiyang & Xu, Juwei & Song, Qun, 2017. "Heterogeneous preference selection promotes cooperation in spatial prisoners’ dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 100(C), pages 20-23.
    9. Gaudeul, Alexia & Keser, Claudia & Müller, Stephan, 2021. "The evolution of morals under indirect reciprocity," Games and Economic Behavior, Elsevier, vol. 126(C), pages 251-277.
    10. Ben-Ner, Avner & Putterman, Louis & Kong, Fanmin & Magan, Dan, 2004. "Reciprocity in a two-part dictator game," Journal of Economic Behavior & Organization, Elsevier, vol. 53(3), pages 333-352, March.
    11. Engelmann, Dirk & Fischbacher, Urs, 2009. "Indirect reciprocity and strategic reputation building in an experimental helping game," Games and Economic Behavior, Elsevier, vol. 67(2), pages 399-407, November.
    12. Andrew W. Bausch, 2014. "Evolving intergroup cooperation," Computational and Mathematical Organization Theory, Springer, vol. 20(4), pages 369-393, December.
    13. Suzuki, Shinsuke & Akiyama, Eizo, 2008. "Evolutionary stability of first-order-information indirect reciprocity in sizable groups," Theoretical Population Biology, Elsevier, vol. 73(3), pages 426-436.
    14. Molina, José Alberto & Ferrer, Alfredo & Gimenez-Nadal, José Ignacio & Gracia-Lazaro, Carlos & Moreno, Yamir & Sanchez, Angel, 2016. "The Effect of Kinship on Intergenerational Cooperation: A Lab Experiment with Three Generations," IZA Discussion Papers 9842, Institute of Labor Economics (IZA).
    15. Liang, Pinghan & Meng, Juanjuan, 2016. "Favor transmission and social image concern: An experimental study," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 63(C), pages 14-21.
    16. Lv, Shaojie & Wang, Xianjia, 2020. "The impact of heterogeneous investments on the evolution of cooperation in public goods game with exclusion," Applied Mathematics and Computation, Elsevier, vol. 372(C).
    17. Shen, Chen & Li, Xiaoping & Shi, Lei & Deng, Zhenghong, 2017. "Asymmetric evaluation promotes cooperation in network population," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 391-397.
    18. Mirko Duradoni & Mario Paolucci & Franco Bagnoli & Andrea Guazzini, 2018. "Fairness and Trust in Virtual Environments: The Effects of Reputation," Future Internet, MDPI, vol. 10(6), pages 1-15, June.
    19. Gary Bolton & Ben Greiner & Axel ockenfels, 2015. "Conflict resolution vs. conflict escalation in online markets," Discussion Papers 2015-19, School of Economics, The University of New South Wales.
    20. Marco Casari, 2002. "Can genetic algorithms explain experimental anomalies? An application to common property resources," UFAE and IAE Working Papers 542.02, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jas:jasssj:2009-36-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Francesco Renzini (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.