5 Investment Dispute Settlement in the African Continental Free Trade Area: Finding a Fit for Purpose Mechanism for the Continent
Bibliographic record
Abstract
Abstract The African Continental Free Trade Area (AfCFTA) represents a transformative milestone in Africa’s economic integration, with investment dispute settlement emerging as a critical pillar for fostering intra-African trade and investment. This paper explores the investment dispute resolution landscape within the AfCFTA, advocating for a harmonized dispute settlement mechanism tailored to the continent’s unique economic and legal realities. It critically examines Africa’s experiences with Investor-State Dispute Settlement ( ISDS ), highlighting grievances related to cost, legitimacy, and limited African representation in arbitration. The study further evaluates regional dispute settlement frameworks within African Regional Economic Communities ( REC s), assessing their successes and limitations in resolving investment disputes. Additionally, it conducts a comparative analysis of investment dispute settlement models outside Africa, including the United States-Mexico-Canada Agreement ( USMCA ), the Comprehensive and Progressive Agreement for Trans-Pacific Partnership ( CPTPP ), and the Investment Court System ( ICS ) under the EU-Canada Comprehensive Economic and Trade Agreement ( CETA ). Drawing lessons from these systems, this paper proposes a harmonized continental arbitration framework for the AfCFTA, incorporating both ISDS and State-to-State Dispute Settlement ( SSDS ), the establishment of regional arbitration centers, an appellate mechanism, and a judiciary supportive of arbitral decisions. The findings emphasize that a well-structured investment dispute settlement system under the AfCFTA is essential for enhancing investor confidence, promoting economic growth, and ensuring Africa’s economic integration objectives are met.
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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 | 0.018 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".