IDEAS home Printed from https://ideas.repec.org/a/mhr/jinste/urndoi10.1628-jite-2020-0006.html
   My bibliography  Save this article

Judicial and Clinical Decision-Making under Uncertainty

Author

Listed:
  • Charles F. Manski

Abstract

Norms for judicial and clinical decisions under uncertainty differ. When clinicians are uncertain about patient health, they view the patient as a member of a population with similar attributes and make care decisions using available knowledge about the distribution of health in this population. In contrast, legal systems typically do not permit a defendant to be convicted of a crime based on a justification that persons with similar attributes often commit this crime. This paper examines the implications if, emulating clinical practice, judges making conviction decisions were to use knowledge of rates of crime commission.

Suggested Citation

  • Charles F. Manski, 2020. "Judicial and Clinical Decision-Making under Uncertainty," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 176(1), pages 33-43.
    • Handle: RePEc:mhr:jinste:urn:doi:10.1628/jite-2020-0006
    DOI: 10.1628/jite-2020-0006
    as

    Download full text from publisher

    File URL: https://www.mohrsiebeck.com/en/article/judicial-and-clinical-decision-making-under-uncertainty-101628jite-2020-0006
    Download Restriction: Fulltext access is included for subscribers to the printed version.
    File URL: https://libkey.io/10.1628/jite-2020-0006?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 search for a different version of it.

    Citations

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


    Cited by:

    1. Manski, Charles F., 2023. "Probabilistic prediction for binary treatment choice: With focus on personalized medicine," Journal of Econometrics, Elsevier, vol. 234(2), pages 647-663.

    More about this item

    Keywords

    judges and clinicians; reasonable decisions under uncertainty; probability thresholds; frequentist and subjective probability;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • K14 - Law and Economics - - Basic Areas of Law - - - Criminal Law
    • K40 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - General

    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:mhr:jinste:urn:doi:10.1628/jite-2020-0006. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Thomas Wolpert (email available below). General contact details of provider: https://www.mohrsiebeck.com/jite .

    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.