Ts’a7inwa (gooseneck barnacles) as a proxy for archaeological efforts to understand shellfish as food in Nuu-chah-nulth territories
Bibliographic record
Abstract
This thesis examines the comparative abundance of shellfish from archaeological assemblages on the west coast of Vancouver Island in Nuu-chah-nulth territories. Eighteen sites spanning the Nuu-chah-nulth region emphasize the diversity in invertebrate foods that have been consumed 5000-150 years ago: Yaksis Cave, Loon Cave, and Hesquiat Village at Hesquiat Harbour; Chesterman Beach; Spring Cove; Ts’ishaa, Ch’ituukwachisht (North and South), Tl’ihuuw’a, Shiwitis, Huumuuwaa, Maktl7ii, Huts’atswilh, Kakmakimilh, Kiix7iin, and Huu7ii. Invertebrate zooarchaeology is an understudied field that has the potential to impact ecological restoration and conservation efforts. Ubiquity, or frequency of occurrence, provides a measure of abundance for a target taxa or species through a percent presence/absence approach. Regionally conventional methods of invertebrate analysis, including weight-based quantification, primarily favour heavy and robust bivalves, such as clams and mussels, and diminish the presence of other frequently occurring invertebrates. Ubiquity-based quantification shows how frequently ‘other’ shellfish have been utilized over time and across archaeological deposits. Gooseneck barnacles (Pollicipes polymerus) are often considered rare, an unimportant intertidal resource, but ubiquity-based analyses show that they are far more abundant than previously appreciated. A methodological combination of these two approaches shows vastly different perspectives on shellfish abundance, and this has implications for how the dietary role of shellfish is understood and discussed in archaeological discourse.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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".