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Public debates driven by incomplete scientific data: The cases of evolution theory, global warming and H1N1 pandemic influenza

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  • Galam, Serge

Abstract

Public debates driven by incomplete scientific data where nobody can claim absolute certainty, due to the current state of scientific knowledge, are studied. The cases of evolution theory, global warming and H1N1 pandemic influenza are investigated. The first two are of controversial impact while the third is more neutral and resolved. To adopt a cautious balanced attitude based on clear but inconclusive data appears to be a lose-out strategy. In contrast overstating arguments with incorrect claims which cannot be scientifically refuted appears to be necessary but not sufficient to eventually win a public debate. The underlying key mechanisms of these puzzling and unfortunate conclusions are identified using the Galam sequential probabilistic model of opinion dynamics (Galam, 2002 [4], Galam, 2005 [18], Galam and Jacobs, 2007 [19]). It reveals that the existence of inflexible agents and their respective proportions are the instrumental parameters to determine the faith of incomplete scientific data in public debates. Acting on one’s own inflexible proportion modifies the topology of the flow diagram, which in turn can make irrelevant initial supports. On the contrary focusing on open-minded agents may be useless given some topologies. When the evidence is not as strong as claimed, the inflexibles rather than the data are found to drive the opinion of the population. The results shed a new but disturbing light on designing adequate strategies to win a public debate.

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  • Galam, Serge, 2010. "Public debates driven by incomplete scientific data: The cases of evolution theory, global warming and H1N1 pandemic influenza," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3619-3631.
  • Handle: RePEc:eee:phsmap:v:389:y:2010:i:17:p:3619-3631
    DOI: 10.1016/j.physa.2010.04.039
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    References listed on IDEAS

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    Cited by:

    1. Galam, Serge, 2023. "Identifying a would-be terrorist: An ineradicable error in the data processing?," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    2. Cheng, Chun & Luo, Yun & Yu, Changbin, 2020. "Dynamic mechanism of social bots interfering with public opinion in network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    3. Galam, Serge, 2011. "Collective beliefs versus individual inflexibility: The unavoidable biases of a public debate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(17), pages 3036-3054.
    4. Leifeld, Philip, 2018. "Polarization in the social sciences: Assortative mixing in social science collaboration networks is resilient to interventions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 510-523.
    5. Galam, Serge, 2021. "Will Trump win again in the 2020 election? An answer from a sociophysics model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    6. Aleksejus Kononovicius & Vygintas Gontis, 2014. "Herding interactions as an opportunity to prevent extreme events in financial markets," Papers 1409.8024, arXiv.org, revised May 2015.
    7. F. Jacobs & S. Galam, 2019. "Two-Opinions-Dynamics Generated By Inflexibles And Non-Contrarian And Contrarian Floaters," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-30, June.
    8. Barreira da Silva Rocha, André, 2013. "Evolutionary dynamics of nationalism and migration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(15), pages 3183-3197.
    9. Dong Jiang & Qian Wang & Zhihua Bai & Heyuan Qi & Juncai Ma & Wenjun Liu & Fangyu Ding & Jing Li, 2020. "Could Environment Affect the Mutation of H1N1 Influenza Virus?," IJERPH, MDPI, vol. 17(9), pages 1-9, April.
    10. Kononovicius, Aleksejus, 2021. "Supportive interactions in the noisy voter model," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    11. Pires, Marcelo A. & Crokidakis, Nuno, 2017. "Dynamics of epidemic spreading with vaccination: Impact of social pressure and engagement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 167-179.
    12. Delanoë, Alexandre & Galam, Serge, 2014. "Modeling a controversy in the press: The case of abnormal bee deaths," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 93-103.

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