Economic access influences degenerative spine disease outcomes at rural Late Medieval Villamagna (Lazio,<scp>IT</scp>)
Bibliographic record
Abstract
OBJECTIVES: Degenerative joint disease in the spine is heavily influenced by genetic, environmental, and epigenetic factors, as well as exacerbated by physical activity and injury. The objective of this study was to investigate the multivariate relationship between known predictors of degenerative joint disease in the spine, such as age and sex, with mortuary indicators of economic access such as grave inclusions, burial location, and burial type. MATERIALS AND METHODS: The presence and severity of vertebral osteophytosis (VO) and vertebral osteoarthritis (VOA) was recorded for the vertebral columns of N = 106 adult individuals from the Late Medieval period at the rural monastery of San Pietro at Villamagna in Lazio, Italy (1300-1450 AD). Multiple skeletal indicators of degenerative joint disease, morphological sex, and age were compared with differences in mortuary treatment across four regions of the spine. RESULTS: There are marked differences in severe joint disease outcome between groups with more and less economic access. Relative risk ratios suggest that males and females with less economic access have elevated risk for VO and VOA in specific spine regions, although this effect is reduced among females. DISCUSSION: Current research on the consequences of economic and social inequality point to the important role of economic inequality in shaping disease outcomes. Our results suggest that biocultural effects of reduced economic access at the intraclass level may increase vulnerability to the downstream effects of risk exposure (e.g., biomechanical injure, physical activity, biochemical imbalance), and ultimately increase the risk and prevalence for severe degenerative disease outcomes in medieval Italy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".