IDEAS home Printed from https://ideas.repec.org/a/eee/jcjust/v98y2025ics0047235225000716.html

Skepticism in science and punitive attitudes

Author

Listed:
  • Rydberg, Jason
  • DeZago, Luke

Abstract

This study examines whether there is an association between skepticism in science and punitive attitudes, including temporal dynamics and potential for unobserved confounding. Drawing on data from the General Social Survey (GSS) repeated cross-sections (1972–2018) (N = 26,652) and 2006–2010 3-wave panels (N = 5807), study objectives were addressed using Bayesian hierarchical age-period-cohort characteristics (HAPC) and hybrid parameterized mixed effect panel logit regression models. Findings suggest that respondents who express skepticism in science are more likely to endorse harsher punishments from courts and a reduction in funding for drug rehabilitation, after controlling for relevant theoretical and empirical controls. This association increases in magnitude across respondent ages, and has been relatively stable over time. Though respondents more likely to be skeptical in science are also more punitive, the association may be partially spurious, potentially reflecting common underlying factors, rather than through a direct causal pathway. The findings underline the challenges in developing consensus on criminal justice policy reform through appeals to evidence-based practices.

Suggested Citation

  • Rydberg, Jason & DeZago, Luke, 2025. "Skepticism in science and punitive attitudes," Journal of Criminal Justice, Elsevier, vol. 98(C).
  • Handle: RePEc:eee:jcjust:v:98:y:2025:i:c:s0047235225000716
    DOI: 10.1016/j.jcrimjus.2025.102422
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047235225000716
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jcrimjus.2025.102422?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. David A. Penn, 2007. "Estimating Missing Values from the General Social Survey: An Application of Multiple Imputation," Social Science Quarterly, Southwestern Social Science Association, vol. 88(2), pages 573-584, June.
    2. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    3. Romer, Daniel & Jamieson, Kathleen Hall, 2021. "Conspiratorial thinking, selective exposure to conservative media, and response to COVID-19 in the US," Social Science & Medicine, Elsevier, vol. 291(C).
    4. Nan, Xiaoli & Wang, Yuan & Thier, Kathryn, 2022. "Why do people believe health misinformation and who is at risk? A systematic review of individual differences in susceptibility to health misinformation," Social Science & Medicine, Elsevier, vol. 314(C).
    5. Ethan Fosse & Christopher Winship, 2019. "Bounding Analyses of Age-Period-Cohort Effects," Demography, Springer;Population Association of America (PAA), vol. 56(5), pages 1975-2004, October.
    Full references (including those not matched with items on IDEAS)

    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. Noémi Kreif & Richard Grieve & Iván Díaz & David Harrison, 2015. "Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1213-1228, September.
    2. Abhilash Bandam & Eedris Busari & Chloi Syranidou & Jochen Linssen & Detlef Stolten, 2022. "Classification of Building Types in Germany: A Data-Driven Modeling Approach," Data, MDPI, vol. 7(4), pages 1-23, April.
    3. Boonstra Philip S. & Little Roderick J.A. & West Brady T. & Andridge Rebecca R. & Alvarado-Leiton Fernanda, 2021. "A Simulation Study of Diagnostics for Selection Bias," Journal of Official Statistics, Sciendo, vol. 37(3), pages 751-769, September.
    4. Lin Lin & Rachel L Spreng & Kelly E Seaton & S Moses Dennison & Lindsay C Dahora & Daniel J Schuster & Sheetal Sawant & Peter B Gilbert & Youyi Fong & Neville Kisalu & Andrew J Pollard & Georgia D Tom, 2024. "GeM-LR: Discovering predictive biomarkers for small datasets in vaccine studies," PLOS Computational Biology, Public Library of Science, vol. 20(11), pages 1-23, November.
    5. Rapp, Hannah & Fredrick, Stephanie & Nickerson, Amanda, 2025. "Cyber victimization reports between parents and children: an examination of agreement predictors," Children and Youth Services Review, Elsevier, vol. 177(C).
    6. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    7. Liangyuan Hu & Lihua Li, 2022. "Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series," IJERPH, MDPI, vol. 19(23), pages 1-13, December.
    8. Norah Alyabs & Sy Han Chiou, 2022. "The Missing Indicator Approach for Accelerated Failure Time Model with Covariates Subject to Limits of Detection," Stats, MDPI, vol. 5(2), pages 1-13, May.
    9. Feldkircher, Martin, 2014. "The determinants of vulnerability to the global financial crisis 2008 to 2009: Credit growth and other sources of risk," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 19-49.
    10. Simon Schmidbauer & Maria Becker & Sonja Haug, 2024. "Online Political Participation of Refugees in Germany: Analysis of a Survey in Bavaria," SAGE Open, , vol. 14(4), pages 21582440241, October.
    11. repec:plo:pone00:0154450 is not listed on IDEAS
    12. Eunsil Seok & Akhgar Ghassabian & Yuyan Wang & Mengling Liu, 2024. "Statistical Methods for Modeling Exposure Variables Subject to Limit of Detection," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(2), pages 435-458, July.
    13. Ida Kubiszewski & Kenneth Mulder & Diane Jarvis & Robert Costanza, 2022. "Toward better measurement of sustainable development and wellbeing: A small number of SDG indicators reliably predict life satisfaction," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 139-148, February.
    14. Georges Steffgen & Philipp E. Sischka & Martha Fernandez de Henestrosa, 2020. "The Quality of Work Index and the Quality of Employment Index: A Multidimensional Approach of Job Quality and Its Links to Well-Being at Work," IJERPH, MDPI, vol. 17(21), pages 1-31, October.
    15. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.
    16. Esef Hakan Toytok & Sungur Gürel, 2019. "Does Project Children’s University Increase Academic Self-Efficacy in 6th Graders? A Weak Experimental Design," Sustainability, MDPI, vol. 11(3), pages 1-12, February.
    17. J M van Niekerk & M C Vos & A Stein & L M A Braakman-Jansen & A F Voor in ‘t holt & J E W C van Gemert-Pijnen, 2020. "Risk factors for surgical site infections using a data-driven approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-14, October.
    18. Stefkovics, Ádám & Krekó, Péter & Koltai, Júlia, 2024. "When reality knocks on the door. The effect of conspiracy beliefs on COVID-19 vaccine acceptance and the moderating role of experience with the virus," Social Science & Medicine, Elsevier, vol. 356(C).
    19. Joost R. Ginkel, 2020. "Standardized Regression Coefficients and Newly Proposed Estimators for $${R}^{{2}}$$R2 in Multiply Imputed Data," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 185-205, March.
    20. Lara Jehi & Xinge Ji & Alex Milinovich & Serpil Erzurum & Amy Merlino & Steve Gordon & James B Young & Michael W Kattan, 2020. "Development and validation of a model for individualized prediction of hospitalization risk in 4,536 patients with COVID-19," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-15, August.
    21. Rawan Omar & Sooyun Caroline Tavolacci & Lathan Liou & Dillan F Villavisanis & Yoav Y Broza & Hossam Haick, 2024. "Real-time prognostic biomarkers for predicting in-hospital mortality and cardiac complications in COVID-19 patients," PLOS Global Public Health, Public Library of Science, vol. 4(3), pages 1-17, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:eee:jcjust:v:98:y:2025:i:c:s0047235225000716. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jcrimjus .

    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.