Cultivating Place: Western Basin Food Production and Landscape Construction in Southwestern Ontario, A.D. 1000–1300.
Bibliographic record
Abstract
This dissertation explores the landscape construction and food production practices at the Western Basin Arkona sites (A.D. 1000–1300) in southwestern Ontario. Paleoethnobotanical analyses of samples from Van Bree (AgHk-32), Figura (AgHk-52), Bingo Village (AgHk-42), and Inland West Pit Location 3 (AgHk-54), Location 4 (AgHk-55), Location 6 (AgHk-56), Location 9 (AgHk-58), and Location 12 (AgHk-60) provide new insights on Younge phase maize cultivation in the region. The study reveals that we must reject the dichotomous subsistence and settlement practices that archaeologists have long mobilized to distinguish Western Basin from Iroquoian communities at this time. Maize was unequivocally the most prevalent taxa recovered from these sites. Maize morphology, kernel and cupule ratios, and the diverse array of early successional species present at these sites indicate that maize cultivation was central to food production, and that maize was not imported but grown locally. I argue that these landscape construction endeavours led to new relationships with weedy species, and I explore the agency of plants like bramble and sumac in shaping increasingly agricultural landscapes. I argue that placemaking practices within maize fields at Arkona reflect a historically contingent and localized tradition built upon generations of ancestral ecological knowledge and ways of being, influenced in part by their environment, surrounding communities, and ideology.
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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 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".