Bibliographic record
Abstract
The Five Major Tribes of the Southeastern United States were removed to Indian Territory, Oklahoma. Indian Territory was a location created to contain all tribal peoples of the U. S. inside it, and then to have walls built around it so none could escape. It was not considered a state. The tribes, in need of assistance promised and denied by the Americans, signed a treaty with the Confederate States of the South. Still, they were removed from their rich lands to the drought-ridden grasslands which became called Oklahoma, our word meaning “Red People”, in 1927. The migration of the people was made difficult as they invaded the land of tribal peoples already present. They needed to learn new trees, had fewer water sources, and lacked knowledge of new medicinal plants. This paper is an account of that migration, even changes created for wildlife and birds, the new knowledge of plants, trees, and especially how new medicines were traded and learned. The stories are spoken by people. A historical memory, and also the stories of continued displacement by government actions and punishments against those who didn’t want to participate in wars soon undertaken. The presenter is from this nation, works there, and hears the stories people continue to tell. From an early age, she also had a mentor in medicinal knowledge, which she doesn’t use except as occasional recommendations.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.016 | 0.017 |
| Insufficient payload (model declined to judge) | 0.030 | 0.007 |
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".