Farmers with a Taste for Fish: New Insights into Iroquoian Foodways at the Dawson Site
Bibliographic record
Abstract
Abstract Iroquoian groups inhabiting the St. Lawrence Valley in the fifteenth and sixteenth centuries AD practiced agriculture and supplemented their diet with fish and a variety of wild plants and terrestrial animals. Important gaps remain in our knowledge of Iroquoian foodways, including how pottery was integrated to culinary practices and the relative importance of maize in clay-pot cooking. Lipid analyses carried out on 32 potsherds from the Dawson site (Montreal, Canada) demonstrate that pottery from this village site was used to prepare a range of foodstuffs—primarily freshwater fish and maize, but possibly also other animals and plants. The importance of aquatic resources is demonstrated by the presence of a range of molecular compounds identified as biomarkers for aquatic products, whereas the presence of maize could only be detected through isotopic analysis. Bayesian modeling suggests that maize is present in all samples and is the dominant product in at least 40% of the potsherds analyzed. This combination of analytical techniques, applied for the first time to Iroquoian pottery, provides a glimpse into Iroquoian foodways and suggests that sagamité was part of the culinary traditions at the Dawson site.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".