Bibliographic record
Abstract
Abstract A few years ago, I attended a slide-illustrated lecture on “Blackfeet Sacred Geography” presented by a member of the Blackfeet tribe. As lights lowered in the room and views of magnificent Montana and Alberta landscapes lit up the screen, Curly Bear Wagner described the events that made these places sacred. He explained where and how the Beaver Bundle came to the Blackfeet. He talked about Scarface and the Sun Dance. While Wagner displayed pictures of the sacred places, seemingly unchanged over the years, and related his peoples’ connection to them, my mind drifted to Walter McClintock who, exactly one hundred years before Wagner’s lecture, walked into a Blackfeet camp and found his life’s calling. McClintock was one of those turn-of-the-century types who concluded the Blackfeet, and other Indians, could not survive in the twentieth century. So, he set about filling notebooks with Indian stories, legends, and descriptions of ceremonies. He spent several years photographing the Blackfeet of Montana and Canada in various poses. In time, McClintock put together his own lantern-slide-illustrated lectures and went on the road, regaling audiences with stories of how the Blackfeet acquired the Beaver Bundle and tales of Scarface and the Sun Dance. He believed that without such efforts as his, all traces of Blackfeet culture would disappear forever.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.565 | 0.390 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".