Indigenous Peoples and the Great Lakes in North America
Bibliographic record
Abstract
Human relationships with the Great Lakes Basin Ecosystem were regulated by various treaties and governance systems for thousands of years prior to European colonization. During these millennia, the waters and surrounding lands of the region were maintained in a healthy state that provided a wealth of benefits to all human and non-human inhabitants. During the relatively short period since colonization, the ecosystem has suffered extensive degradation, with indigenous peoples suffering a disproportionate level of health and economic impacts as a result. Binational agreements such as the Great Lakes Water Quality Agreement between the United States and Canada have for decades been concerned with maintaining and restoring the water quality of the region, but have only recently come to recognize the importance of indigenous rights, responsibilities and knowledge with respect to the area. This recognition is welcome and long overdue, but continues to fall short of respecting an indigenous voice on a nation-to-nation basis. In order for indigenous perspectives to be meaningfully applied to the protection of Great Lakes waters, indigenous peoples must be afforded the opportunity to work collaboratively with other interests on Great Lakes protection initiatives from their inception, rather than trying repeatedly - and often ineffectively - to provide mere “input” into existing non-indigenous frameworks. A summary of indigenous concerns with respect to the Great Lakes environment is offered as a starting point for discussion around the development of a more meaningful collaboration.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".