A study on the Canadian mining industry and the potential for the “Duty to Consult” as a pathway towards reconciliation with Indigenous Peoples: lessons for Brazil
Bibliographic record
Abstract
Using a reconciliation framework, this research examines select Canadian case law and the \nevolution of the “duty to consult” to explore the potential lessons for resource extraction in \nBrazil. It conducts an analysis of the legal precedents that exist in Canadian common law as they \nrelate to Indigenous communities and apply the framework drawn to the resource extraction \nprocess with the hope of determining best practices. In Canada, ongoing discussions and \nchallenges about the importance of land to Indigenous Communities, their culture and traditions \nare commonplace, but in Brazil, legal precedents and policies do not appear as well developed. \nIndigenous land claims and resource extraction decisions at the countries’ top courts are of \ncritical importance to both nations given that mining development impacts upon the social, \neconomic, and cultural aspects of Indigenous Peoples in both countries. This research targets \nlegal policies, commentary and Court decisions in Canada relating to Indigenous land and the \nmining industry, with an emphasis on constitutional law, to compare aspects of land claims and \nconstitutional rulings and how they have influenced social policy on Indigenous lives in regards \nto reconciliation. There are constructive lessons for the Brazilian government emerging from the \ncomparison regarding how Canadian constitutional law has framed Indigenous rights with regard \nto resource development. In this research, I have found in my analysis that the “duty to consult” \nit’s an important key element in the path for reconciliation with the Indigenous communities. \nThis study revealed the influence of colonial social structures that still persevere and directly \naffect Indigenous communities in contemporary society.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.033 | 0.013 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".