Licensing by modification: The case of French<b><i>de</i></b>nominals
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
The aim of this paper is to provide an analysis of the positive effect that modification has on the distribution of noun phrases in otherwise illicit environments. I focus on de nominals in French. By focusing on these nominals, whose distribution is altered by the addition of modifiers, the paper shows that modifiers can do much more than simply modify: they can change the syntactic and semantic status of a noun phrase. The licensing property of modifiers is an intriguing topic and has not been greatly discussed in the literature. I argue that modifiers can come to play the role of determiners in French as long as they are accompanied by a head de , which is the spell-out of a Cardinal head (see Lyons 1999). My proposal goes back to an old idea put forward by Damourette & Pichon (1911–1940) according to which, in modified contexts, de functions as one half of the article while the adjective functions as the other half. More generally, articles in French are seen as dual entities comprising of a specifier and a head. In the absence of the determiner les , an adjective can raise to the specifier of CardinalP. This is achieved via phrasal rather than head movement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| 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