Book Review of <i>Imagining Head-Smashed-In: Aboriginal Buffalo Hunting on the Northern Plains</i> By Jack W. Brink
Bibliographic record
Abstract
Jack Brink has written an important and engaging book, his personal tribute to the Head-Smashed-In Buffalo Jump in southern Alberta, Canada. This is an easy-going, almost conversational narrative, but it’s easy to detect the author’s passion and the solid science that lies behind his simple words. Imagining Head-Smashed-In boasts a remarkably broad and well-crafted table of contents. Brink begins with an overview of Head-Smashed-In, patiently explaining to professional and lay reader alike why this particular archaeological site should command our attention. As an admitted zealot, he doesn’t shy away from occasional hyperbole: “If hunters of the Plains were engaged in the most rewarding procurement of food ever devised by human being, maybe life wasn’t so bad after all.” In Brink’s view, this cliff face and “simple lines of rocks” ranks right up there with, say, Stonehenge and the Great Wall of China; this is, after all, one of fewer than 900 places designated by UNESCO as a “World Heritage Site.” The stage then shifts to the main character, the American buffalo (or, as Brink points out, more properly called the North American bison). Two chapters chronicle the biology, life history, and especially seasonal behavior of “the great beast of the Plains.”
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.041 | 0.014 |
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".