Balance between Investment Protection and Sustainable Development under Tanzania-Canada BITs: Need for Progressive Domestic Investment Law
Bibliographic record
Abstract
Interactions between foreign investment and host community raise questions as to the proper approach to balance investment protection and sustainable development interests. This article examines how Tanzania balances investment protection with social and environmental concerns. Tanzania has had a mixed practice with foreign investment and Bits. Few Bits were concluded in the early years after independence. But then the country experimented with socialism and self-reliance in late 1960’s and 1970’s, only to reverse trend in mid-1980’s. Tanzania concluded majority of her Bits in 1990s and 2000’s. From 2010, Tanzania concluded Bits which are conscious of sustainable development concerns. Tanzania-Canada BIT is a case in point. These Bits not only inserted explicit sustainable development provisions but also progressive investment standard provisions which afford the government space to regulate legitimate sustainable development objectives. However, this recalibration approach still faces practical challenges due inconsistencies of arbitral tribunals. To help fill this gap, the study considers the role of domestic investment laws in protecting sustainable development interests. In that regard, the study holds the view that domestic investment laws have to be sustainable development oriented in order to supplement other approaches of balancing investor rights with sustainable development interests of host states.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".