Analyse comparée des cadres législatifs et conventionnels de la fiscalité aurifère en Afrique de l'Ouest
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
L'Afrique est riche en ressources minérales. Le continent est réputé concentrer 30 % des réserves mondiales de matières premières minières. Dans les années 1990, la Banque mondiale s'inquiétait que « l'Afrique profite moins que l'Amérique latine et l'Asie de l'exportation minière pour doper sa croissance : les compagnies minières privées la boudent en y investissant moins de 5% des dépenses d'exploration mondiale ». Après plusieurs décennies, les pays africains ont vu l'intérêt des investisseurs miniers pour le continent croître. Ainsi, en 2009, l'Afrique représentait 15 % des budgets d'exploration (hors uranium) pour les métaux non ferreux, une part légèrement supérieure à l'Australie (13 %) et inférieure au Canada (16 %).
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it