Body proportions of circumpolar peoples as evidenced from skeletal data: Ipiutak and Tigara (Point Hope) versus Kodiak Island Inuit
Bibliographic record
Abstract
Given the well-documented fact that human body proportions covary with climate (presumably due to the action of selection), one would expect that the Ipiutak and Tigara Inuit samples from Point Hope, Alaska, would be characterized by an extremely cold-adapted body shape. Comparison of the Point Hope Inuit samples to a large (n > 900) sample of European and European-derived, African and African-derived, and Native American skeletons (including Koniag Inuit from Kodiak Island, Alaska) confirms that the Point Hope Inuit evince a cold-adapted body form, but analyses also reveal some unexpected results. For example, one might suspect that the Point Hope samples would show a more cold-adapted body form than the Koniag, given their more extreme environment, but this is not the case. Additionally, univariate analyses seldom show the Inuit samples to be more cold-adapted in body shape than Europeans, and multivariate cluster analyses that include a myriad of body shape variables such as femoral head diameter, bi-iliac breadth, and limb segment lengths fail to effectively separate the Inuit samples from Europeans. In fact, in terms of body shape, the European and the Inuit samples tend to be cold-adapted and tend to be separated in multivariate space from the more tropically adapted Africans, especially those groups from south of the Sahara.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".