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 paper is aimed at defining the concepts needed in the discussion of so-called ‘support (≈ light) verbs’ and presenting a way of describing them in the lexicon in terms of Lexical Functions [= LFs]. It develops the following six points : 1. A genuine support verb is semantically empty (or ‘emptied’ in the context of its keyword). 2. There are just three types of ‘pure’ support verbs — Oper, Func, and Labor — distinguished according to the syntactic role fulfilled by their keyword. 3. Two sorts of meanings are often combined with support verbs : phasic meanings (‘begin,’ ‘stop,’ ‘continue’) and causative meanings (‘cause’) ; such a meaning plus a support verb form a complex LF. 4. There exist other sorts of meanings (especially, intensification) that can bear on the predicative noun but are expressed together with the support verb : they form, with the latter, a configuration of LFs. 5. A family of semantically full collocational verbs show the same syntactic behavior as support verbs : these are called realization verbs. 6. Using support verbs and their encoding in terms of LFs, it is possible to construct a universal Deep-Syntactic paraphrasing system. Several examples of DSynt-paraphrasing rules are given. The discussion is carried out based on French.
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 | 0.000 | 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 | 0.000 | 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) | 0.006 | 0.001 |
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