Analyzing Dispersion

Gries, Stefan Τh.

doi:10.1007/978-3-030-46216-1_5

Cited by 42 publications

(14 citation statements)

References 24 publications

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“…Therefore, many such studies will be anticonservative and overestimate the importance of between-variety differences. In addition, virtually none of the studies that use frequencies or frequency differences of features Y to make a theoretical point consider the dispersion of Y in the corpus although it has been shown that underdispersion can invalidate any corpus statistic (Gries, 2008(Gries, , 2020.…”

Section: Statistical Issuesmentioning

confidence: 99%

Theoretical models and statistical modelling of linguistic epicentres

2022

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Motivated by a fundamental discussion of the relation between theoretical and statistical modelling, the present paper takes stock of the research history of linguistic epicentres in the world Englishes paradigm and seeks to provide suggestions for future epicentral studies. Based on a review of earlier research into potential epicentral constellations, we provide an overview of the genesis of the concept of linguistic epicentres, describe different methodological approaches that have been chosen and/or recommended for their study and provide statistical comments. With a view to future epicentral research, we aim at (i) refining the theoretical construct of linguistic epicentres, (ii) suggesting empirical methods that allow identifying epicentral constellations more reliably than in the past and (iii) making statistical recommendations particularly relevant to epicentral research.

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Section: Statistical Issuesmentioning

confidence: 99%

Theoretical models and statistical modelling of linguistic epicentres

2022

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“…Dispersion (Gries, 2008(Gries, , 2020(Gries, , 2021 measures how equally widespread a given ABB word is across all three corpus data types, and can be viewed as a sort of correction on raw frequencies. For instance, do some words only appear in the institutionalized dictionary data or are they used relatively equally in social media data and traditional corpus material as well?…”

Section: Methodsmentioning

confidence: 99%

What ratings and corpus data reveal about the vividness of Mandarin ABB words

Van Hoey,

Yu,

Pan

et al. 2024

Lang. cogn.

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A well-known method of studying iconic words is through the collection of subjective ratings. We collected such ratings regarding familiarity, iconicity, imagery/imageability, concreteness, sensory experience rating (SER), valence and arousal for Mandarin ABB words. This is a type of phrasal compound consisting of a prosaic syllable A and a reduplicated BB part, resulting in a vivid phrasal compound, for example, wù-mángmáng 雾茫茫 ‘completely foggy’. The correlations between the newly collected ABB ratings are contrasted with two other sets of prosaic word ratings, demonstrating that variables that characterize ABB words in an absolute sense may not play a distinctive role when contrasted with other types of words. Next, we provide another angle for looking at ABB words, by investigating to what degree rating data converges with corpus data. By far, the variable that characterizes ABB items consistently throughout these case studies is their high score for imageability, showing that they are indeed rightfully characterized as vivid. Methodologically, we show that it pays off to not take rating data at face value but to contrast it with other comparable datasets of a different phenomenon or data about the same phenomenon compiled in an ontologically different manner.

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“…The scores given above are the result of partitioning COCA into 100 parts, and so it may be that a term like "justify" or "know" is in fact quite unevenly distributed but that this is not reflected by the score. Biber et al (2016) recommend instead using Gries' DP (Gries 2008(Gries , 2019 and Gries himself has made this score (and a range of other dispersion scores) available for all word forms in the BNC. 14 Gries' DP (with a lower score indicating that the term is more widely distributed) for the various word forms for "justify" and "know" are shown in Table 2.…”

Section: Distributionmentioning

confidence: 99%

Justification: Insights from Corpora

Grindrod

2022

Episteme

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In this paper I use insights from exploratory analyses on large English language corpora to consider the extent to which there is a widely used ordinary notion of justification that attaches to beliefs. I will show that this has ramifications for one broad approach to theorising about justification – the folk justification approach. I will argue that the corpus-based findings presented pose a challenge to the folk justification approach insofar as they suggest that “justify” is not widely used talk about the justification of our beliefs. I will conclude by presenting the possible solutions to this challenge, and remarking on their feasibility.

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Analyzing Dispersion

Cited by 42 publications

References 24 publications

Theoretical models and statistical modelling of linguistic epicentres

Theoretical models and statistical modelling of linguistic epicentres

What ratings and corpus data reveal about the vividness of Mandarin ABB words

Justification: Insights from Corpora

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