IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v13y2023i4p21582440231197025.html
   My bibliography  Save this article

A Domain-Function Analysis of ni zhidao (ä½ çŸ¥é “, “You Know†) in Chinese Simultaneous Speech

Author

Listed:
  • Yi Shan

Abstract

Most theoretical and empirical studies of discourse marker multifunctionality do not approach it using a formal, systematic annotation model. Drawing on a domain-function taxonomy, this study examines 270 tokens of the discourse marker ni zhidao in Chinese media interviews. All values of the two-dimensional model designed for the whole category of discourse markers apply to ni zhidao , demonstrating its equally potent affordance on a particular discourse marker case cross-linguistically. By putting this model to the test, we found that “emphasis†needs to be added to the original 15 functions in the model, and that domains and functions need to be treated as dependent layers of pragmatic meaning. Functions determine domains, and domains need to be regarded as macro-functions to which specific functions are attributed. As such, we tentatively put forth an updated version that provides finer granularity and greater affordance, shedding new light on the pragmatic meaning of ni zhidao and the speaker’s underlying communicative intent. We propose that the sample be divided into uni-functional and multi-functional categories before being analyzed within the updated model to capture the multifunctional discourse markers in the same context-specific utterances. This study has implications for the need of more exhaustive, speech-friendly annotation models of DM multifunctionality and the cross-linguistic adaptation or refinement of established DM annotation models to cater to the unique traits of spoken DMs in different languages.

Suggested Citation

  • Yi Shan, 2023. "A Domain-Function Analysis of ni zhidao (ä½ çŸ¥é “, “You Know†) in Chinese Simultaneous Speech," SAGE Open, , vol. 13(4), pages 21582440231, October.
  • Handle: RePEc:sae:sagope:v:13:y:2023:i:4:p:21582440231197025
    DOI: 10.1177/21582440231197025
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440231197025
    Download Restriction: no

    File URL: https://libkey.io/10.1177/21582440231197025?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
    ---><---

    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:sae:sagope:v:13:y:2023:i:4:p:21582440231197025. 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: SAGE Publications (email available below). General contact details of provider: .

    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.