Chapter II: <i>The Natives of North America</i>
Bibliographic record
Abstract
Indian Languages. Chepawyans. the Bow. Women. Snow Shoes. wrestling for Women. Grief. Religion. Na hath a way. Language. Metch e Manito. Conjurers. Conjuring hut. Scotchmen. Dances. Weapons. half breed natives. Tents and Duties. Sleds. Moose hunting. Red Deer. Early Marriages. Superstition. Camping Nahathaway's country. Play and gambling. Eap pis tim's Horse. future state. Sussee and Stone Indians, stealing. Peagans. Saddles. Horses. Horses Slays. Wild Horses. Grizled Bear. fatal effects. Marriage. Polygamy. Pipe Stems. Polygamy. Koo tanae Appe. Koo tanae Appe Son. is shot and dies. the Soul immortal. Small Pox. Weapons. tradition on Animals. War. conduct of it. French Canadian shot. death of a french canadian. travel ambuscade. power of Mind. Counting. Males taken. War. Spaniards. Saleesh law of Adultry. Battle. Finan. Mitchel. My Canoes intercepted. My retreat. 3 bears. Pee a gans & Snake Indians. Snake camp destroyed. Old Men. Horse Slay. die. Kootanae killed. the cause. future state. Horses & Musketoes. Rain & Rainbow. Locusts. Musketoes. Natives Eastward & Westward. Natives. Aurora Borealis. Languages. Origin. the Soul immortal. Retaliation law. death for his sister. Coal Mines. Porcupine. Dogs. Beaulieu. Anecdotes. Amelle's Dog. Skunk. Peagan Woman suicide. Regret of her husband. Chief's duty. War. Koo tanae Appe. Scalp. No Missionary. Religion of us hard to explain. Feasts. Gambling. May be only pastoral.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.253 | 0.102 |
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".