Scurvy in the Great Irish Famine: Evidence of vitamin C deficiency from a mid‐19th century skeletal population
Bibliographic record
Abstract
Scurvy has increasingly been recognized in archaeological populations since the 1980s but this study represents the first examination of the paleopathological findings of scurvy in a known famine population. The Great Famine (1845-1852) was a watershed in Irish history and resulted in the death of one million people and the mass emigration of just as many. It was initiated by a blight which completely wiped out the potato-virtually the only source of food for the poor of Ireland. This led to mass starvation and a widespread occurrence of infectious and metabolic diseases. A recent discovery of 970 human skeletons from mass burials dating to the height of the famine in Kilkenny City (1847-1851) provided an opportunity to study the skeletal manifestations of scurvy-a disease that became widespread at this time due to the sudden lack of Vitamin C which had previously almost exclusively been provided by the potato. A three-scale diagnostic reliance approach has been employed as a statistical aid for diagnosing the disease in the population. A biocultural approach was adopted to enable the findings to be contextualized and the etiology and impact of the disease explored. The results indicate that scurvy indirectly influenced famine-induced mortality. A sex and stature bias is evident among adults in which males and taller individuals displayed statistically significantly higher levels of scorbutic lesions. The findings have also suggested that new bone formation at the foramen rotundum is a diagnostic criterion for the paleopathological identification of scurvy, particularly among juveniles.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".