« <i>De sur a norte</i> » : traduire la posture <i>ch’ixi </i>de Silvia Rivera Cusicanqui vers l’anglais
Bibliographic record
Abstract
En 2019, dix ans après sa publication originale en espagnol, apparaît le premier livre traduit vers l’anglais de l’activiste, théoricienne, historienne et sociologue bolivienne Silvia Rivera Cusicanqui : Ch’ixinakax utxiwa. On Practices and Discourses of Decolonization (Polity Press). Le contexte de cette traduction est problématique : alors que, dans son texte, Rivera Cusicanqui adresse une forte critique aux théories et théoricien·nes de la décolonisation issu·es des universités nord-américaines, ce sont ces mêmes universités qui la traduisent quelques années plus tard. Cet article propose une analyse de la posture (Meizoz, 2009) de Rivera Cusicanqui qui se développe à partir du concept aymara ch’ixi, une couleur grise constituée d’un noir et d’un blanc qui ne se mélangent pas. L’étude de quelques extraits de Ch’ixinakax utxiwa. On Practices and Discourses of Decolonization servira à démontrer que la posture auctoriale est transformée dans le processus traductif, où certains de ses traits sont effacés ou nuancés, et que ces transformations sont indissociables du contexte de production de la traduction.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".