Bibliographic record
Abstract
Malheureusement, l’economie du don dans le systeme capitaliste-patriarcal est discreditee et retenue invisible. Un changement vers un paradigme feministe est necessaire. Selon l’auteur, la premiere etape consiste a devoiler la pratique de l’economie du don et a se demander pourquoi elle n’a jamais ete consideree comme valable. L’auteur identifie l’economie du don, non seulement, dans la pratique maternelle mais aussi dans la langue elle-meme et note que le don a ete annule en tant que cle d’interpretation par la linguistique et la semiotique comme par de nombreuses autres disciplines academiques. Ensuite, elle reconnait un lien entre les modeles de donner et de recevoir des humains et ceux des niches environnementales de la nature, insistant sur le fait que si nous acceptons l’economie du don, lui-meme vu, comme donation qui a besoin d’un receveur, nous pourrons tout interpreter selon ce paradigme, comme le font certaines cultures des peuples autochtones qui souvent pratiquent le don. L’article se termine sur la question de l’importance du modele maternel pour realiser un changement social radical.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".