Bacon, Joséphine ; Kanapé-Fontaine, Natasha et Pésémapéo-Bordeleau, Virginia. (2021). Mujer Tierra, Mujer Poema. Sara, María Leonor y Zaparart, María Julia (coord.). Traducción de Maivé Habarnau et al. Editorial Malisia
Bibliographic record
Abstract
Mujer Tierra, Mujer Poema, c'est le titre de cette puissante anthologie poétique bilingue français-espagnol qui accueille trois représentantes féminines des littératures autochtones d'expression française des Premiers Peuples de Québec : Joséphine Bacon, Natasha Kanapé-Fontaine et Virginia Pésémapéo-Bordeleau. ;Il s'agit du fruit du travail collectif mené au sein du Département de Langues et Littératures Modernes de la Faculté des Humanités et Sciences de l'Education de l'Université Nationale de La Plata, à l'intérieur du Laboratoire de Recherches en ;Traductologie (LIT) de l'Institut de Recherches en Humanités et Sciences Sociales, avec le soutien de l'Organisation Internationale de la Francophonie et de la maison d'édition Malisia de la ville de La Plata, Argentine. De plus, les coordinatrices remercient spécialement les contributions d'Ana María Gentile, Jean-François Létourneau, Christine Sioui Wawanoloath et Rodney Saint-Éloi.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.089 | 0.045 |
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".