Exploring the introduction of European dogs to North America through shoulder height
Bibliographic record
Abstract
Abstract The introduction of domesticated species to new environments has been used to identify colonisation events in the archaeological record but rarely provides the opportunity to investigate colonists' selection of particular breeds or stock. This analysis employs morphometrics, the measurement of skeletal landmarks, supported by historic documentation to explore the intersection between colonists' breed preferences and species translocation. In doing so, this analysis provides insight into the differential effects of human selective breeding on domestic dog's ( Canis familiaris ) physical characteristics in Native American and European societies. Historic sources suggest that European colonists selectively imported large dog breeds capable of defending settlements and livestock, acting as war dogs, and aiding hunters. Colonists' dogs are reputed to have been significantly larger than Native American dogs. This study compares standardised measurements taken on bones to estimate shoulder height. We find that dog populations in England and North America spanning the period 0–1,800 AD exhibit an almost identical average stature; however, the range of shoulder height variation in European dogs is far greater than seen in eastern Native American dog populations. Dogs in colonial American contexts are statistically larger than both Native American and European dog populations, supporting documentary accounts that colonists selectively imported breeds from the largest available in Europe.
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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 | 0.001 | 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".