Canadian Investment Treaties with African Countries: What Do They Tell Us About Investment Treaty Making in Africa?
Bibliographic record
Abstract
Between 2013 and 2015, Canada signed nine bilateral investment treaties (BITs) with countries in Africa. Canada was remarkably successful in imposing its model investment treaty on its African partners. Canada’s success might be considered surprising. Investor-state arbitration cases have shown the strong binding character of BITs and the corresponding need for host states to ensure that treaties reflect their distinctive priorities. In seeking to do so, African countries could have looked to African regional initiatives for expressions of made in African investment policies. African negotiators could have benefited from the substantial work done by UNCTAD and others to provide new forms of international investment rules that make BITS more supportive of sustainable development. Despite stronger incentives for African countries to assert themselves in BIT negotiations and resources for them to draw on, however, Canada’s recent BITs suggest that political and economic power continue to define the outcome of negotiations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".