IMF Programs and Economic Growth in the DRC: Documentation, Impact and Prospects
Bibliographic record
Abstract
At the end of 2012 the International Monetary Fund (IMF) has suspended its financial assistance to the Democratic Republic of the Congo (DRC). Due to inflationary pressures which occurred in the last quarter of 2016, several decision-makers called for a reopening of a formal cooperation with the IMF. This process was formally completed in December 2019. The restart of IMF programs was greeted with satisfaction by politicians and widely commented in the media. However, recent history shows that the DRC managed to achieve exceptional economic performance, between 2012 and 2016, without being in a formal cooperation with the IMF. Some people wonder whether IMF assistance is a curse for recipient countries? We argue that the underlying problem has nothing to do with accepting or not the IMF assistance, but rather in the ability of policy makers to establish effective leadership and good governance for the development and implementation supporting structural reforms.
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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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.014 | 0.039 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".