ISOTOPIC ANALYSES REVEAL GEOGRAPHICAL AND SOCIOECONOMIC PATTERNS IN HISTORICAL DOMESTIC ANIMAL TRADE BETWEEN PREDOMINANTLY WHEAT- AND MAIZE-GROWING AGRICULTURAL REGIONS IN EASTERN NORTH AMERICA
Bibliographic record
Abstract
Historical zooarchaeologists have made significant contributions to key questions about the social, economic, and nutritional dimensions of domestic animal use in North American colonial contexts; however, techniques commonly employed in faunal analyses do not offer a means of assessing many important aspects of how animals were husbanded and traded. We apply isotopic analyses to faunal remains from archaeological sites to assess the social and economic importance of meat trade and consumption of local and foreign animal products in northeastern North America. Stable carbon and nitrogen isotope analyses of 310 cattle and pigs from 18 rural and urban archaeological sites in Upper Canada (present-day southern Ontario, Canada; ca. A.D. 1790–1890) are compared with livestock from contemporary American sources to quantify the importance of meat from different origins at rural and higher- and lower-status urban contexts. Results show significant differences between urban and rural households in the consumption of local animals and meat products acquired through long-distance trade. A striking pattern in urban contexts provides new evidence for the social significance of meat origins in historical Upper Canada and highlights the potential for isotopic approaches to reveal otherwise-hidden evidence for social and economic roles of animals in North American archaeology.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 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".