Bibliographic record
Abstract
DPs with quantity nouns (QDPs), like that amount of nuts, can combine with predicates of quantities, as in That amount of nuts is low, or with predicates of entities, as in Bo ate that amount of nuts. One account of such selectional flexibility, inspired by Selkirk (1977) and Rothstein (2009), assumes that the two types of predication are transparently encoded through two types of syntactic structures. In this paper, we draw attention to a syntactic challenge for this account of QDPs, viz.that in certain cases it requires two interpreted occurrences of an entity noun like nuts even though only one is pronounced. We argue, however, that this challenge mustbe met and cannot be avoided by abandoning the structural approach. We make this case by arguing against an alternative analysis of the selectional flexibility of QDPs developed in Scontras 2017. On this alternative, quantity predication and entity predication with QDPs are derived from a uniform syntax, and entity predication with QDPs parallels entity predication with DPs with kind, like that kind of nuts, under the classic Carlsonian account (Carlson 1977) as developed in Chierchia 1998. We argue that Scontras’ analysis is mistaken, both in positing a unified syntax for the two types of predication with QDPs, and in unifying the analysis of QDPs withthe Carlsonian analysis of kind-DPs.
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".