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Article published In:
Journal of Second Language Studies
Vol. 5:2 (2022) ► pp.171–205

What do (most of) our dispersion measures measure (most)? Dispersion?

| University of California, Santa Barbara , USA | JLU Giessen

This paper discusses the degree to which most of the most widely-used measures of dispersion in corpus linguistics are not particularly valid in the sense of actually measuring dispersion rather than some amalgam of a lot of frequency and a little dispersion. The paper demonstrates these issues on the basis of data from a variety of corpora. I then outline how to design a dispersion measure that only measures dispersion and show that (i) it indeed measures information that is different from frequency in an intuitive way and (ii) has a higher degree of predictive power of lexical decision times from the MALD database than nearly all other measures in nearly all corpora tested.

Keywords: dispersion, frequency, association, range, Juilland’s D , Gries’s DP , generalized additive modeling
Article outline
  • 1.Introduction
  • 2.A brief recap: G 2 reacts more to frequency than to association
  • 3.Dispersion measure: What do they measure and how?
    • 3.1Existing measures
    • 3.2A new measure: Motivation and development
    • 3.3Perspective 1: DP nofreq measures dispersion, not frequency
    • 3.4Perspective 2: DP nofreq helps predicting external data
  • 4.Two short excurses
    • 4.1Excursus 1 range nofreq
    • 4.2Excursus 2: fast bowler vs. fast food
  • 5.Concluding remarks
  • Notes
  • References
Published online: 30 November 2021
DOI logo
https://doi.org/10.1075/jsls.21029.gri
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