Argument structure licensing and English<b>have</b>
Why this work is in the frame
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Bibliographic record
Abstract
This paper provides a unified syntactic account of the distribution of English have in causative constructions (e.g. John had Mary read a book ) and experiencer constructions (e.g. John had the student walk out of his classroom ). It is argued that have is realized in the context of an applicative head (Appl) and an event-introducer v, regardless of the type of v. Have is spelled out in the causative when Appl merges under v CAUSE , and in the experiencer construction when Appl merges under v BE . This proposal is extended to have in possessive constructions (e.g. John has a hat / a brother ): have is realized in the context of v BE and Appl. The proposed account provides empirical evidence for expanding the distribution of Appl: (i) a causative can take ApplP as a complement, which was absent in Pylkkänen's (2008) typological classification, and (ii) Appl can merge above Voice, contrary to Pylkkänen's analysis in which Appl is argued to always merge below VoiceP, never above. Moreover, the proposed account supports the theoretical claim that argument structure is licensed by functional syntactic structure; in particular, it shows that the relevant functional heads are not aspectual heads, but Appl and v.
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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 | 0.006 |
| 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