@cite{woodin-etal-2023}: Numeral Frequency and Roundness #
@cite{sigurd-1988} @cite{woodin-etal-2023}
Corpus study showing number frequency is predicted by: (a) log magnitude, and (b) graded roundness via Sigurd/Jansen & Pollmann k-ness properties.
Key finding: each k-ness property has an independent positive effect on frequency, with 10-ness being the strongest predictor and multipleOf5 the weakest.
Register Effect #
Informational texts (Wikipedia) show stronger roundness effects than non-informational texts (fiction, conversation), suggesting roundness interacts with communicative goals.
Regression coefficient for each k-ness property on log frequency.
Higher β = stronger positive effect on numeral frequency in corpora. All coefficients are positive: each property independently increases frequency.
- property : String
- β : ℚ
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β coefficients ordered by magnitude (Table 3).
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- WoodinEtAl2024.β_tenness = { property := "10-ness", β := 446 / 100 }
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- WoodinEtAl2024.β_2_5ness = { property := "2.5-ness", β := 384 / 100 }
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- WoodinEtAl2024.β_5ness = { property := "5-ness", β := 261 / 100 }
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- WoodinEtAl2024.β_2ness = { property := "2-ness", β := 156 / 100 }
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- WoodinEtAl2024.β_mult10 = { property := "multipleOf10", β := 52 / 100 }
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- WoodinEtAl2024.β_mult5 = { property := "multipleOf5", β := 6 / 100 }
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The 6 coefficients in descending order.
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Frequency-weighted roundness score using Woodin et al.'s β coefficients.
Unlike the unweighted roundnessScore (which counts properties equally),
this weights each property by its empirical frequency effect.
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weightedRoundnessScore 50 > 0: 50 has multipleOf5, multipleOf10,
2.5-ness, and 5-ness, so its weighted score is the strictly positive
sum of those β coefficients.
RSA utterance prior from corpus frequency. Rounder numerals have
higher prior weight, so weightedRoundnessScore doubles as an
empirically-grounded RSA utterance prior: rounder numerals are more
likely to be chosen, all else equal. The strict-monotonicity chain
100 > 50 > 7 realises this on representative cases.
Register type from corpus analysis.
Informational registers (Wikipedia) show stronger roundness effects than non-informational registers (fiction, conversation).
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- WoodinEtAl2024.instReprRegister = { reprPrec := WoodinEtAl2024.instReprRegister.repr }
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- WoodinEtAl2024.instDecidableEqRegister x✝ y✝ = if h : x✝.ctorIdx = y✝.ctorIdx then isTrue ⋯ else isFalse ⋯
Register effect datum: roundness β is larger in informational texts.
- register : Register
- roundnessEffectMagnitude : String
- notes : String
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