IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0058910.html
   My bibliography  Save this article

Quantitative Analysis of Gender Stereotypes and Information Aggregation in a National Election

Author

Listed:
  • Michele Tumminello
  • Salvatore Miccichè
  • Jan Varho
  • Jyrki Piilo
  • Rosario N Mantegna

Abstract

By analyzing a database of a questionnaire answered by a large majority of candidates and elected in a parliamentary election, we quantitatively verify that (i) female candidates on average present political profiles which are more compassionate and more concerned with social welfare issues than male candidates and (ii) the voting procedure acts as a process of information aggregation. Our results show that information aggregation proceeds with at least two distinct paths. In the first case candidates characterize themselves with a political profile aiming to describe the profile of the majority of voters. This is typically the case of candidates of political parties which are competing for the center of the various political dimensions. In the second case, candidates choose a political profile manifesting a clear difference from opposite political profiles endorsed by candidates of a political party positioned at the opposite extreme of some political dimension.

Suggested Citation

  • Michele Tumminello & Salvatore Miccichè & Jan Varho & Jyrki Piilo & Rosario N Mantegna, 2013. "Quantitative Analysis of Gender Stereotypes and Information Aggregation in a National Election," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-10, March.
    • Handle: RePEc:plo:pone00:0058910
    DOI: 10.1371/journal.pone.0058910
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0058910
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0058910&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0058910?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
    ---><---

    Citations

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


    Cited by:

    1. Puccio, Elena & Pajala, Antti & Piilo, Jyrki & Tumminello, Michele, 2016. "Structure and evolution of a European Parliament via a network and correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 167-185.

    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:plo:pone00:0058910. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.