Bibliographic record
Abstract
Nous sommes au Burkina, en pays lobi, lors d’un grand rituel de fécondité. L’ethnologue effectue une mission de terrain avec son jeune fils. On nous apprend que notre chienne (Bellina) est atteinte d’un mal foudroyant. On pourrait alléger sa souffrance à l’aide de soins palliatifs. L’enfant pleure celle qu’il considère comme une sorte de petite soeur. Les Lobi, mis au courant de cette situation, recommandent au contraire de tuer au plus vite Bellina afin d’en faire une bonne soupe, cynophagie oblige. Deux modes de représentations, d’affects et de comportements se retrouvent soudain mis en écho, discutés et commentés. Ils seront ici analysés à l’aide de narrations graphiques, de brèves de terrain recueillies dans le hors-champ de l’enquête et de récits aux allures de mythe. Mis en dialogues, ces éléments discursifs accentuent autant la violence de ces déliaisons croisées qu’ils mettent en évidence des liaisons vitales inattendues unissant l’homme au chien, en France comme au Burkina.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.109 | 0.014 |
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".