De l’usage de fonds mythiques dans les remaniements territoriaux en Afrique et au Cameroun
Bibliographic record
Abstract
Outils de conception et de transcription des remaniements territoriaux, les cartes européennes du XVe au XXe siècle donnent à voir les facettes mythiques qui ont présidé au façonnement occidental des États africains et les discours éthiques que leur émergence suscite. En Afrique, les mythes épiques indigènes permettent de comprendre comment les populations comme celles du Cameroun ont vécu le partage spatial. C'est parce qu'ils n'échappent ni à l'instrumentalisation morale ni au façonnement épique que les remaniements territoriaux donnent lieu au déploiement d'une pensée où mythes éthiques et épiques servent de toile de fond. En effet, la production des territoires favorise le recours à l'imaginaire et au fantastique autant qu'elle suscite des manipulations idéologiques et leur dénonciation. Les mythes s'avèrent ainsi de puissants moyens interactifs de gestion et de connaissance de la complexité géographique et de la complication sociopolitique.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".