Exploring the multidimensionality of stature variation in the past through comparisons of archaeological and living populations
Bibliographic record
Abstract
Adult stature variation is commonly attributed to differential stress-levels during development. However, due to selective mortality and heterogeneous frailty, a population's tall stature may be more indicative of high selective pressures than of positive life conditions. This article examines stature in a biocultural context and draws parallels between bioarchaeological and living populations to explore the multidimensionality of stature variation in the past. This study investigates: 1) stature differences between archaeological populations exposed to low or high stress (inferred from skeletal indicators); 2) similarities in growth retardation patterns between archaeological and living groups; and 3) the apportionment of variance in growth outcomes at the regional level in archaeological and living populations. Anatomical stature estimates were examined in relation to skeletal stress indicators (cribra orbitalia, porotic hyperostosis, linear enamel hypoplasia) in two medieval bioarchaeological populations. Stature and biocultural information were gathered for comparative living samples from South America. Results indicate 1) significant (P < 0.01) differences in stature between groups exposed to different levels of skeletal stress; 2) greater prevalence of stunting among living groups, with similar patterns in socially stratified archaeological and modern groups; and 3) a degree of regional variance in growth outcomes consistent with that observed for highly selected traits. The relationship between early stress and growth is confounded by several factors-including catch-up growth, cultural buffering, and social inequality. The interpretations of early life conditions based on the relationship between stress and stature should be advanced with caution.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".