Weaker bones and white skin as adaptions to improve anthropological “fitness” for northern environments
Bibliographic record
Abstract
The vitamin D paradox relates to the lower risk of osteoporosis in people of sub-Saharan African ancestry (Blacks) compared with people of European ancestry (Whites). The paradox implies that for bone health, Blacks require less vitamin D and calcium than Whites do. Why should populations that migrated northward out of Africa have ended up needing more vitamin D than tropical Blacks? Human skin color became lighter away from the tropics to permit greater skin penetration of the UVB light that generates vitamin D. Lack of vitamin D impairs intestinal calcium absorption and limits the amount of calcium that can deposit into the protein matrix of bone, causing rickets or osteomalacia. These can cause cephalopelvic disproportion and death in childbirth. Whiter skin was more fit for reproduction in UV-light restricted environments, but natural selection was also driven by the phenotype of bone per se. Bone formation starts with the deposition of bone-matrix proteins. Mineralization of the matrix happens more slowly, and it stiffens bone. If vitamin D and/or calcium supplies are marginal, larger bones will not be as fully mineralized as smaller bones. For the same amount of mineral, unmineralized or partially mineralized bone is more easily deformed than fully mineralized bone. The evidence leads to the hypothesis that to minimize the soft bone that causes pelvic deformation, a decrease in amount of bone, along with more rapid mineralization of osteoid improved reproductive fitness in Whites. Adaptation of bone biology for reproductive fitness in response to the environmental stress of limited availability of vitamin D and calcium came at the cost of greater risk of osteoporosis later in life.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".