War and Predatory Economy in Northern-Kenya: How Ethnomusicology Can Explore Social Change
Bibliographic record
Abstract
La pratique des vols de bétail entre populations pastorales et agro-pastorales a constitué, probablement pendant des siècles, une des formes principales d’activité militaire en Afrique de l’Est ainsi qu’un dispositif incontournable pour la construction du masculin à l’échelle locale. À la moitié des années 1990, dans le Samburu County, au nord du Kenya, un afflux soudain et imposant d’armes automatiques provenant des territoires en guerre de la partie orientale du continent a produit un changement radical des anciens paradigmes de mise en place des razzias. Chez les communautés samburu du mont Nyiro le bouleversement profond des pratiques du conflit a altéré les relations politico-hiérarchiques entre les membres des statuts d’âge des « guerriers » et des anciens en entraînant une alliance militaire aux proportions inédites. L’activité musicale cérémonielle, témoin inattendu de cette transformation, constitue un des espaces d’interaction au sein desquels les nouveaux agencements du système d’âge émergent de manière explicite et sont reproduits dans le temps.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".