Riding for a fall: Bone fractures among mounted archers from the Hungarian Conquest period (10th century CE)
Bibliographic record
Abstract
Abstract Horse riding, a determinant activity in the history of human cultural evolution, remains unreliably identifiable from the analysis of human skeletal remains due to various sample and methodological limitations. Through a comparison between well‐documented series of presumed riders and non‐riders, this study aimed to investigate the link between skeletal fractures and that practice in past populations. We relied on a Hungarian Conquest period population (Sárrétudvari‐Hízóföld, Hungary, 10th century CE) known to be composed of mounted archers. We recorded the presence of acute fractures on the main bones of the upper and lower skeleton to analyze their distribution and perform comparisons between the individuals with or without riding‐related deposits in their grave and with an out‐sample group of presumed non‐riders from the documented Luís Lopes Skeletal Collection (Lisbon). We observed more fractures in the Hungarian series and especially higher rates concerning the upper limb, while the distribution of traumas was more homogenous in the documented collection. There were also significantly more clavicle fractures in the Hungarian group with riding deposit than in the non‐riders from Lisbon, whose type can be related to a fall from a height. Our results coincide with sports medicine data on equestrians, whose injuries mostly concern the upper limbs. Such traumas, and especially clavicle fractures, are often caused, indeed, by a fall from a horse. Through the use of pertinent anthropological series, this study provides the most reliable association between the presence of skeletal traumas and the practice of horse riding in a past population.
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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 | 0.000 |
| 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 | 0.000 |
| 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".