Native American studies in higher education: models for collaboration between universities and indigenous nations
Bibliographic record
Abstract
Chapter 1 Introduction: Defining Indian Studies Through Stories and Nation Building Chapter 2 Chapter 1: Eleazar Wheelock Meets Luther Standing Bear: Native American Studies at Dartmouth College Chapter 3 Chapter 2: American Indian Studies at the University of Oklahoma Chapter 4 Chapter 3: American Indian Studies at the University of California-Los Angeles Chapter 5 Chapter 4: Culture, Tradition and Evolution: The Department of Native Studies at Trent University Chapter 6 Chapter 5: American Indian Studies at the University of Arizona Chapter 7 Chapter 6: A Hemispheric Approach to Native American Studies at the University of California-Davis Chapter 8 Chapter 7: In Caleb's Footsteps: The Harvard University Native American Program Chapter 9 Chapter 8: A Story of Struggle and Survival: American Indian Studies at the University of Minnesota-Twin Cities Chapter 10 Chapter 9: The Department of Indian Studies at the Saskatchewan Indian Federated College Chapter 11 Chapter 10: O'ezhichigeyaang (This Thing We Do): American Indian Studies at the University of Minnesota-Duluth Chapter 12 Chapter 11: Standing in the Gap: American Indian Studies at the University of North Carolina-Pembroke Chapter 13 Chapter 12: One University, Two Universes: Alaska Natives and the University of Alaska-Anchorage
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".