Distributive Numerals and Distance Distributivity in Tlingit (and Beyond)
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Bibliographic record
Abstract
This article develops a formal semantic and syntactic analysis of distributive numerals in Tlingit, a highly endangered language of Alaska, British Columbia, and the Yukon. Such numerals enforce a ‘distributive reading’ of the sentence, and thus are one instance of the broader phenomenon of ‘distance distributivity’ (Zimmermann 2002). As in many other languages, a Tlingit sentence containing a distributive numeral can describe two distinct kinds of ‘distributive scenarios’: (i) a scenario where the distribution is over some plural entity (e.g. ‘My sons caught three fish each’), and (ii) one where the distribution is over some plural event (e.g. ‘My sons caught three fish each time’) (Gil 1982, Choe 1987, Zimmermann 2002, Oh 2005). Despite this apparent ambiguity, I put forth a univocal semantics for Tlingit distributive numerals, one whereby they consistently invoke quantification over events. Under this semantics, the ability of distributive numerals to describe both kinds of scenarios in (i) and (ii) is due not to an ambiguity, but instead to the sentences having relatively weak truth conditions. In contrast to prior analyses of distributive numerals and distance distributivity, the proposed semantics does not actually make use of distributive operators, but nevertheless retains a rather conservative picture of the syntax-semantics interface. The analysis can also account for certain locality effects noted for distance distributives in Korean and German (Zimmermann 2002, Oh 2005), as well as an intriguing puzzle regarding distributive numerals and pluractionality in Kaqchikel (Henderson 2011). Finally, I show how the analysis can be extended to the well-known case of English ‘binominal each’.*
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it