Discours de revendication de femmes activistes dans les médias : (auto-)assignations raciales, (contre-)interpellations et positionnement de l’enseignante-chercheure interpellée
Bibliographic record
Abstract
Afin d’établir l’enchainement des interpellations et assignations raciales produit avant, pendant et après la médiatisation de revendications anti-racistes, cet article fait l’analyse critique de deux paroles de femmes activistes françaises d’ascendance sub-saharienne (malienne-sénégalaise) et algérienne et des articles en ligne qui les ont diffusées. L’étude des déclarations de ces activistes et des backlashes des instances institutionnelles (médias et représentants politiques), tels qu’entextualisés et hypertextualisés dans les articles étudiés, puis de commentaires individuels (commentateurs, lecteurs, etc.), met en lumière la polarisation entre ces revendications et les réactions qu’elles suscitent. Pour finir, j’interroge ma position d’enseignante-chercheure qui, adoptant une lecture raciolinguistique (Rosa et Flores 2017) des médias dans un contexte sociétal agité, se trouve elle-même doublement interpellée et prend alors part à un nouvel ordre (pédagogique) d’interpellation.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.017 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".