Bibliographic record
Abstract
Keller uses anthropometric measurement to examine the health of Native American children attending the Perris Indian School of Southern California during the last decade of the nineteenth century. She compares the mean stature of children at Perris with similar historical and contemporary populations and analyzes their nutrition and linear patterns which reflect on the health of given populations. In accordance with anthropometric research, the taller the population, the better the population's overall health. Keller shows that in comparison to other populations, the children attending Perris Indian School would be considered the "tallest in the world." Such a conclusion contradicts research in this volume by Trafzer and Hyer. Keller questions her findings. She argues that Native parents clearly privileged their children in terms of food, but that the methodology she employs does not take into consideration variables such as genetics, ethnicity, or culture. Administrators screened students attending the school to exclude those with illnesses or physical disabilities. The healthiest children attended Perris while the remainder of the Native population in the region was under stress due to government policies and poverty.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".