Collecte des données, protection des sources et production des savoirs sur Boko Haram en contexte de paranoïa sécuritaire au Cameroun
Bibliographic record
Abstract
La présente contribution est un retour réflexif sur les modalités de production et de publication des données sensibles au cours d’une recherche ethnographique dans les prisons, les casernes et certaines localités camerounaises touchées par les exactions de Boko Haram et les affres des pratiques contre-insurrectionnelles de l’armée, entre 2014 et 2021. Il y est question des modalités de mise en œuvre d’une éthique située dans un contexte national de vide juridique et institutionnel. Ce travail traite également des contraintes méthodologiques et des dilemmes éthiques rencontrés pendant l’observation directe et les entretiens. La question des outils de recherche et de leur fonctionnalité est également abordée. Enfin, ce travail aborde les problématiques des contre-dons attendus du chercheur, de la protection des participants à l’enquête et de la sécurisation des données sensibles.
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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 | 0.018 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".