Re-examining the mass-count distinction
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This paper argues that the mass-count distinction does not represent a fundamental division between the world's languages. We demonstrate that such a distinction, as commonly defined within the linguistic literature, often conflates two facts: the semantic fact, found in all languages, that some words have atomic denotations and some do not, and the morphosyntactic fact, found in languages with contrasting singular-plural morphology, that some nouns have both singular and plural forms while others have only one such form. By comparing English with Mandarin Chinese, we discuss whether this morphosyntactic distinction might correlate with the presence or absence of a rich classifier system (as well as other types of quantification). This potential correlation has greatly influenced how linguists have investigated nominal systems across languages and it has even led some to hypothesize that morphosyntactic subcategories might determine the ways in which a grammar can “count” and “quantify.” We outline some important exceptions to this proposed correlation in languages such as Ch’ol, Mi’gmaq and Western Armenian. The paper concludes by arguing not only that there is no such correlation, but that linguists should rethink how they investigate nominal systems, focusing more on lexical variation (even within a single language) than on parametric variations across languages.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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