Graduate studies at Western
Philosophy of Science 78 (5):788-799 (2011)
|Abstract||This paper motivates using explicit methods in linguistics by attempting to estimate the size of a linguistic data set. Such estimations are diﬃcult because redundant data can easily pad the data set. To address this, I oﬀer some explicit operationalizations of the data and their features. But for linguistic data, negative associations don’t indicate true redundancy, and yet for many measures they can be mathematically impossible to ignore. It is proven that this troublesome phenomenon has positive Lebesgue measure, is monotonically increasing, and that these two features hold robustly in four diﬀerent ways|
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