The Chad-Cameroon Pipeline Project--Assessing the World Bank's Failed Experiment to Direct Oil Revenues towards the Poor
Bibliographic record
Abstract
The World Bank's engagement with projects involving extractive industries has not proven particularly successful. Especially in Sub-Saharan Africa, it has actually often made matters worse. Borrower countries' economies failed to grow, and corruption increased; the poor did not benefit from the revenues that were generated. This paper assesses the complex legal and institutional framework of the World Bank project that many hoped would change this bleak record: in the highly publicized and controversial Chad-Cameroon Pipeline Project, the Bank catalyzed the largest private investment in the history of Sub-Saharan Africa. This model project featured new and untested contractual, statutory, institutional and fiscal mechanisms which were intended to make Chad's oil revenues transparent and compel the Government of Chad—one of the world's poorest—to expend its oil revenues on areas consistent with the project's agreed poverty reduction objective, such as education and health. Despite these heroic measures, in 2008 the revenue allocation program collapsed, and the Bank's projects in Chad terminated prematurely. Not for the first time, the government of Chad had unilaterally altered the underlying laws to enable more security and military spending. Yet again, the poor had not profited from the oil revenues. We analyse in this paper whether the Bank's failure in the Chad-Cameroon Pipeline Project was due to specific errors in the framework of contracts, laws and institutional structures the Bank deployed—errors which could, in theory, be taken as lessons for a future project making use of an improved revenue allocation system—or whether generally the Bank's entire concept of contractually imposing a revenue allocation system is flawed, such that any attempt to revive such a system on another occasion is misguided and futile.
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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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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 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".