IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/sw7nz_v1.html
   My bibliography  Save this paper

Personal Narratives Build Trust Across Ideological Divides

Author

Listed:
  • Hagmann, David

    (The Hong Kong University of Science and Technology)

  • Minson, Julia A.
  • Tinsley, Catherine

Abstract

Lack of trust is a key barrier to collaboration in organizations and is exacerbated in contexts when employees subscribe to different ideological beliefs. Across five preregistered experiments, we find that people judge ideological opponents as more trustworthy when opposing opinions are expressed through a self-revealing personal narrative than through either data or stories about third parties---even when the content of the messages is carefully controlled to be consistent. Trust does not suffer when explanations grounded in self-revealing personal narratives are augmented with data, suggesting that our results are not driven by quantitative aversion. Perceptions of trustworthiness are mediated by the speaker's apparent vulnerability and are greater when the self-revelation is of a more sensitive nature. Consequently, people are more willing to collaborate with ideological opponents who support their views by embedding data in a self-revealing personal narrative, rather than relying on data-only explanations. We discuss the implications of these results for future research on trust as well as for organizational practice.

Suggested Citation

  • Hagmann, David & Minson, Julia A. & Tinsley, Catherine, 2020. "Personal Narratives Build Trust Across Ideological Divides," OSF Preprints sw7nz_v1, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:sw7nz_v1
    DOI: 10.31219/osf.io/sw7nz_v1
    as

    Download full text from publisher

    File URL: https://osf.io/download/5f7378fd46080904221ad15b/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/sw7nz_v1?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
    ---><---

    More about this item

    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:osf:osfxxx:sw7nz_v1. 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: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    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.