Bibliographic record
Abstract
« L’écriture de Bouraoui est une exploration, couche par couche de l’épaisseur du vocable. En spéléologue averti, il fait corps avec lui, subit les mouvements désordonnés qui s’y créent. » A. Bensmaïn, L’Opinion, Maroc. \n \n« Car Bouraoui, c’est d’abord le ‘citoyen du monde’ ‘poreux à tous les souffles’, dont la poésie fait éclater les cadres ‘nationaux étriqués’ pour s’élever aux dimensions de l’univers. Partout où s’élabore un véritable projet humain. Mais Bouraoui, c’est aussi le magicien du verbe. » Jérôme Carlos, Ivoire Dimanche, Côte d’Ivoire. \n \n“…an infinitely plural work. We could study indefinitely its tendencies and multiplicities. We could exalt the shades, listen to the silences, make the sensations shiver or awaken anger, but above all it is a question of celebrating invention and arriving at the total feast of words.” Cécile Cloutier, Waves, Canada. \n \n“The poet succeeds in using the immediate visual and sensory impressions of the visitor to dramatize a more penetrating portrait of a society and its problems.” Hal Wylie, World Literature Today, U.S.A. \n \n“Absorbed in other cultures the poetic persona is no longer bounded by his own genius or nature but enjoys a wider collective identity.” Liliane Welch, Fiddlehead, Canada.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.386 | 0.205 |
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".