Finding a Duty to Consult Aboriginal Peoples During the Negotiation of Free Trade Agreements (FTAs) and Foreign Investment Promotion and Protection Agreements (FIPAs)
Bibliographic record
Abstract
This article explores whether there is a legal duty to consult with Indigenous groups prior to the ratification of international trade and investment agreements. It considers both the content of the duty to consult and the circumstances under which such a duty is triggered. In doing so, this paper analyzes the arguments of Hupacasth First Nation v Canada, the only case that has been brought to the courts on this issue. Although the Federal Court of Appeal dismissed the Hupacasath First Nation’s claim that the duty to consult extends to negotiations that the federal government enters into with other State governments for Foreign Investment Protection Agreements (FIPAs), the analysis was confined to the particulars of the case. It remains to be seen whether the circumstances may yet exist in which the duty to consult will be found to apply to the negotiation of international trade agreements. To conclude, this paper investigates other potential sources of the duty to consult in law, including First Nations treaties, exemption clauses in Free Trade Agreements and FIPAs, and international obligations to indigenous peoples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.015 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.004 |
| 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".