The Slaughter of the Bison and Reversal of Fortunes on the Great Plains
Bibliographic record
Abstract
Abstract In the late nineteenth century, the North American bison was brought to the brink of extinction in less than two decades. We demonstrate that the loss of the bison had immediate, negative consequences for the Native Americans who relied on them and ultimately resulted in a persistent reversal of fortunes. Once amongst the tallest people in the world, the generations of bison-reliant people born after the slaughter lost their entire height advantage. By the early twentieth century, child mortality was 16 percentage points higher and the probability of reporting an occupation 19 percentage points lower in bison nations compared with nations that were never reliant on the bison. Throughout the latter half of the twentieth century and into the present, income per capita has remained 25% lower, on average, for bison nations. This persistent gap cannot be explained by differences in agricultural productivity, self-governance, or application of the Dawes Act. We provide evidence that this historical shock altered the dynamic path of development for formerly bison-reliant nations. We demonstrate that limited access to credit constrained the ability of bison nations to adjust through re-specialization and migration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".