Identifying National and International Vacuums Potentially Impacting NAFTA and Indigenous Peoples
Bibliographic record
Abstract
The North American Free Trade Agreement (NAFTA) was made among three nation-states, Canada, the United States, and Mexico. Each of these nation-states has indigenous populations within its borders. Each has chosen different legal mechanisms for interacting with indigenous peoples. For example, the United States has an extensive web of treaties with the tribes within its borders while Canada, in contrast, has relatively few. All three nation-states have grappled with armed conflicts with indigenous peoples well into the 20th century. Indigenous peoples within each have long social, cultural, economic, and political histories which cross the borders of these countries. Within the provisions of NAFTA, each nation-state reserved the right to deny investors rights or preferences provided to "aboriginal peoples", "socially or economically disadvantaged minorities", or "socially or economically disadvantaged groups" in from two to five designated areas. All three approaches nevertheless leave substantial national and international legal vacuums that necessarily impact the implementation of NAFTA as well as the economic interests of indigenous peoples. This paper identifies some of those vacuums, considers their potential impacts and their relationship to negotiations on a Free Trade of the Americas (FTAA) agreement, and discusses possible remedies.
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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 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".