The congolese economy in front of the volatility of oil revenues
Bibliographic record
Abstract
L’économie congolaise est confrontée à une crise majeure depuis la chute des prix du pétrole observée à partir de juillet 2014. Le faible niveau des prix du pétrole a eu pour conséquence une diminution considérable des revenus pétroliers, qui a entrainé à son tour une réduction drastique des dépenses et des difficultés de mise en œuvre du plan national de développement. Si les perspectives sur le marché pétrolier laissent transparaitre une certaine amélioration en 2018, il n’en demeure pas moins que le financement du budget de l’Etat reposant essentiellement sur les revenus pétroliers, apparaît de moins en moins en adéquation avec les ambitions du gouvernement de créer les conditions d’une croissance inclusive et durable. La réorientation de la politique budgétaire devrait donc conduire à une diversification des sources de revenus afin de limiter les vulnérabilités financières, budgétaires et économiques liées à la dépendance pétrolière.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".