The relevancy and effectiveness of the United Nations Convention Against Corruption
Bibliographic record
Abstract
La Convention des Nations Unies contre la corruption, adoptée en 2003, est le premier outil international criminalisant la corruption de façon aussi détaillée. Ce mémoire tente d'évaluer sa portée en analysant les dispositions concernant la prévention, la criminalisation, la coopération internationale et le recouvrement d'avoirs. Il tente d’évaluer la pertinence et l'efficacité de la Convention en illustrant ses défis en matière de conformité, pour ensuite étudier d'autres outils internationaux existants qui lui font compétition. Malgré sa portée élargie, il est débattu que la Convention souffre de lacunes non négligeables qui pourraient restreindre son impact à l'égard de la conduite d'États Membres.
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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 | 0.022 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".