Minimally Invasive Research Strategies in Huron-Wendat Archaeology
Bibliographic record
Abstract
ABSTRACT The rapid pace of economic, political, and social change over the past 150 years has framed and reframed archaeological practice in Ontario. Indigenous groups have become increasingly involved in and critical of archaeological research. Indigenous peoples who value archaeological investigation of ancestral sites, but also desire to protect their buried ancestors, have restricted archaeological excavation and the analysis of remains. Over the last decade, research and consulting archaeologists in Ontario, Canada, have worked collaboratively with Indigenous peoples with an eye to developing sustainable archaeology practices. In the spirit of sustainable archaeology, a comprehensive research project and field school run by Wilfrid Laurier University is training the next generation of archaeologists to adopt investigative techniques that minimize disturbance of ancestral sites. Here we present the results of our surface, magnetic susceptibility, and metal detecting surveys of a Huron-Wendat village site, which pose minimally invasive solutions for investigating village sites in wooded areas. The water-sieving of midden soils in an attempt to recover 100 percent of cultural materials, and the analysis of archived collections also honor the values of Indigenous descendant communities by limiting additional invasive excavation.
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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 | 0.002 | 0.002 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".