La nourriture comme métaphore de la voix dans Le Bonheur a la queue glissante d’Abla Farhoud
Bibliographic record
Abstract
Le Bonheur a la queue glissante d’Abla Farhoud donne la parole a la protagoniste, qui ne sait que parler l’arabe et qui est analphabete, afin qu’elle puisse transmettre son experience et trouver sa voix. Dounia a une forte relation avec la nourriture et elle a substitue la nourriture a l’expression orale pendant une grande periode de sa vie. Cuisiner est devenu la contribution de Dounia a sa famille, son moyen d’expression, sa facon de continuer sa culture libanaise et d’y rester fidele. Pas capable d’enseigner a ses enfants et de les « nourrir » avec la langue, Dounia les nourrit avec des repas. Cette communication propose de demontrer comment Farhoud postule que le langage non verbal peut etre aussi important sinon plus que la langue parlee, notamment dans le contexte de l’immigration ou la communication est rendue difficile par les differences marquees entre les membres d’une meme famille.
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 | 0.005 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".