4. Current challenges to the Lexicalist Hypothesis: An overview and a critique
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this chapter, arguments against several variants of the modern syntax-based analyses of deverbal nominalizations are presented, and the classic lexicalist approach deriving from Chomsky’s 1970 Remarks on nominalization is defended. The modern approaches of Alexiadou (2001), Fu, Roeper and Borer (2001), Harley and Noyer (1998), which revive in various forms the sentential Generative Semantics analyses of event nominals, are each considered and rejected in turn. In such approaches, argument-structure nominals contain some amount of verbal structure as a proper subpart. Yet, all such nominals exhibit surface syntactic patterns that resemble exactly those of nonderived nominals. The absence of verb-phrase syntax within nominalizations is a fundamental generalization about such nominals, and is very problematic for analyses which propose such substructure.
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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) | 0.001 | 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