From meteorology to linguistics: what precipitation constructions in English, French and Spanish tell us about arguments, argumenthood, and the architecture of the grammar
Bibliographic record
Abstract
This work takes the variation in syntactic configurations that precipitation verbs display in non-metaphorical contexts in English, French, and Spanish as a case study to examine more general questions about the notions of argument and argumenthood, and how arguments and other elements are introduced in the syntax. It also proposes a unified analysis of such constructions based on a constructivist model (Borer 2005). Specifically, it argues that the syntactic variation attested in this case is a by-product of the combination of general language constraints along with particular features of the functional elements (expletive types), and a general property of the architecture of the grammar: the possibility to merge (and pronounce) the same element in different syntactic positions. The latter explains away: the denominal character of precipitation verbs (Hale & Keyser 1991), thus, the presence of a DP that shares the verb’s root (or a hyponym), and the syntactic and interpretational properties of the DP. In the same vein, some properties and constraints linked to precipitation constructions are reanalyzed as expected outcomes of specific structural configurations, and/or pragmatic effects. The paper also includes a detailed examination of the syntactic evidence that has been put forth to establish the argument status of weather-it, and concludes that once the full interpretation of the syntactic constructions is taken into account, such a claim cannot be justified. Although this work subscribes to the generative tradition, the empirical discussion developed here is relevant beyond this framework.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".