Bibliographic record
Abstract
Par « gérondif non-coréférentiel », nous entendons le gérondif dont le sujet n'est pas coréférentiel avec celui de la proposition régissante. Il s'agit là d'un emploi souvent qualifié d'anomalie grammaticale. Notre enquête dans le corpus « Corpatext 1.02 » a révélé que les conditions prototypiques du gérondif non-coréférentiel étaient (i) les verbes psycho-cognitifs pour le gérondif, et (ii) l'aspect lexical non-borné pour le verbe de la proposition régissante. Nous affirmons par là que c'est le sujet de cognition sous-jacent à la proposition régissante qui est le sujet implicite du gérondif non-coréférentiel, et que ce dernier est une façon d'expression qui reflète le « mode I » selon Nakamura (2009), à savoir un mode de cognition qui pénètre dans la réalité observée. Non-coreferential gérondif Abstract: By "non-coreferential gérondif" I mean the gérondif whose subject is not coreferential with that of the matrix clause. It is often considered grammatically anomalous. Our investigation in the corpus "Corpatext 1.02" revealed that the prototypical conditions of the coreferential gérondif were (i) the psycho-cognitive verb in the gérondif, and (ii) the atelic verb, a verb that expresses an unbounded situation, in the matrix clause. Therefore, it is the subject of cognition implied in the matrix-clause situation that is the implicit subject of non-coreferential gérondif. I argue that this type of gérondif reflects the way of expression with "I" mode in the sens of Nakamura (2009), namely, a mode of cognition with a viewpoint that slips into the observed reality.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".