Distance intertextuelle et connexion lexicale : outils de catégorisation générique ou stylistique ? Approche expérimentale d'un corpus inédit : le corpus aragonien
Bibliographic record
Abstract
The purpose of this paper is to test and to compare various methods used by the statistical analyses of the literary texts to measure the more or less big lexical or grammatical nearness of two corpora. The functions included in Hyperbase, the measure of the "intertextual distance" which is based on the indications of Jaccard and the method of Labbé will so be experimented but also the evaluation of the "lexical connection" which we owe to Ch. Muller. The tree diagrams (X. Luong) which emphasize the classificatory hierarchy of texts will be used in particular to present the distribution of the high and the low frequencies as possible criterion of generic differentiation. The chosen corpus of experiment is an original corpus which groups together the poetic work of Aragon written between 1917 and 1952 and narrative works. It has the double advantage to cross two generic sets and to extend over an important chronological slice. The generic parameter and the chronological variation will so be felt as possible criteria of linguistic and stylistic differentiation of the lemmatized corpus.
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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 | 0.052 | 0.229 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".