Abstract
The previous chapter suggested the possibility that linguistic units that are atomically inseparable, such as words, partly derive from statistical universals of language. Harris’s hypothesis, however, only indicates how words are acquired and does not say anything about their meanings. Thus far, this book has not considered the notion of meaning at all, and the question of what is meaning is one of the most difficult in human history. It nevertheless seems that when we hear a sequence of words, we apprehend an image of its meaning. Hence, this chapter considers how the statistical universals could contribute to the meanings of words.
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Notes
- 1.
The original ratings in the MRC list ranged from 100 to 700, so the scores were divided by 100 here for consistency with the Amano list. Furthermore, the two lists differ in that the Amano list contains only content words, whereas the MRC list also has some functional words. Note that functional words need not be equally familiar. For example, the familiarity of “must” is clearly higher than that of “ought.” The functional words in the MRC list do not necessarily include the most frequently used functional words, such as “and” and “to.”
- 2.
This collection was crawled from the Internet in 2006 (Tanaka-Ishii and Terada, 2011). All the markup tags were eliminated, and texts in English and Japanese were extracted. For English, 265,823,502 pages were scanned to obtain 1.9 terabytes of text data without tags. For Japanese, 12,751,271 pages were scanned to obtain 69 gigabytes of text data without tags. Chapter 22 further describes these corpora.
- 3.
This figure appeared in Tanaka-Ishii and Terada (2011).
- 4.
The figure shows the Pearson correlation coefficient because it is the most well-known such coefficient. Some readers might know that this coefficient measures the linearity of the relationship between two variables. Looking at the plots, however, we can see a nonlinearity that would be better measured by Spearman’s correlation, which was 0.74 for the English data and 0.49 for the Japanese data.
- 5.
The example words were changed for clarity.
- 6.
- 7.
As Sect. 15.2 will explain, a power distribution has the characteristic of remaining a power distribution through various kinds of transformations.
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Tanaka-Ishii, K. (2021). Word Meaning and Value. In: Statistical Universals of Language. Mathematics in Mind. Springer, Cham. https://doi.org/10.1007/978-3-030-59377-3_12
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