Linking structural variability in long bone diaphyses to habitual behaviors: Foragers from the southern African Later Stone Age and the Andaman Islands
Bibliographic record
Abstract
The cross-sectional distribution of cortical bone in long bone diaphyses is highly responsive to mechanical loading during life, yet the relationship between systemic and localized influences on skeletal structure remains unclear. This study investigates postcranial robustness throughout the body among adults from two groups of foragers with different patterns and modes of mobility, to determine whether there is evidence for upper vs. lower body localization of skeletal robustness. The samples used for this comparison are from the southern African Later Stone Age (LSA; n = 65, male = 33, female = 28) dating from ca. 10,000 to 2,000 B.P., and 19th century indigenous Andaman Islanders (AI; n = 36, male = 17, female = 16). The LSA were highly mobile foragers who did not exploit offshore marine resources. In contrast, the AI had tightly constrained terrestrial, but significant marine, mobility. Geometric properties of cortical bone distribution in the diaphyses of the clavicle, humerus, femur, tibia, and first metatarsal are compared between the samples, providing a representation of skeletal robustness throughout the body. Multivariate ANOVA shows the AI to have significantly stronger clavicles and humeri, while the LSA femora, tibiae, and first metatarsals are stronger than those of the AI. These patterns, in which upper and lower limbs show biomechanical properties that are consistent with habitual behaviors, suggest localized osteogenic response. Although postcranial robustness appears to be correlated with overall limb function, the results suggest that more proximal elements within the limb may be more responsive to mechanical loading.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".