Bibliographic record
Abstract
Cette these aborde l'oeuvre d'Ernest J. Gaines, ecrivain afro-americain originaire de Louisiane, autour de tois notions d'identite, de communaute et de langage, en montrant comment sa fiction ouvre un espace de construction d'une communaute de langue, d'histoire et d'histoires, ou l'identite se forge sur le mode intercatif et performatif, en relation constante avec l'autre, qu'il s'agisse du Noir, du Metis ou du Blanc. Elle montre que l'anamnese permet aux Noirs de prendre conscience de la necessite de resister et de se reapproprier leur h/Histoire -une histoire foisonnante se nourrissant des memoires individuelles. L'oeuvre gainesienne se concoit non seulement comme une valorisation extreme de la parole, mais aussi comme un espace dialogique et polyphonique : Ernest J. Gaines est ainsi avant tout un ecrivain de l'oralite, d'un conteur, qui paie sa dette envers la tradition orale en donnant a entendre des voix au sein de son ecriture.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".