Why this work is in the frame
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Bibliographic record
Abstract
This paper is the first investigation of nominal countability in Kaingang, a Jê language spoken in Brazil. The main claim of this paper is that all Kaingang nouns are lexically count. This hypothesis is supported by a number of morphosyntactic and semantic properties of nouns in the language. Among them two crucial properties emerge: (i) Kaingang allows numerals and other count quantity expressions to combine directly with individual and substance nouns, and (ii) in quantity judgement tasks (Barner & Snedeker 2005) comparisons with both types of nouns are cardinality-based. I analyze this generalized counting strategy as a direct effect of the lexical semantics of nouns. Building on Krifka’s approach (1989; 2007; 2008), I argue that all Kaingang nouns are born quantized, i.e., they are lexically equipped with a context-sensitive built-in counting function that measures quantities in terms of individual- or portion-units. This paper contributes with additional crosslinguistic evidence to two claims: (i) that the mass/count distinction in the nominal domain isn’t a language universal (Wiltschko 2012), and (ii) that the defining property of count nouns is quantization, rather than atomicity (Krifka 1989; 2007).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.009 |
| 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