Making kw’éts’tel: A materialization of household food-focused labor
Bibliographic record
Abstract
Salmon fishing and storage have been integral elements of Stó:lō-Coast Salish household life, economy, and identity in the Fraser Valley and lower Fraser Canyon of southwestern British Columbia for millennia. However, taphonomic factors affecting salmon remains make it difficult to directly study variability in food-related labor allocations, prompting us to focus instead on fish processing tools. This study employs experimental archaeology, archaeological collections analyses, and geochemistry to investigate the production of kw’éts’tel—ground slate fish knives essential to the precontact Stó:lō-Coast Salish salmon economy. Our objectives are to examine the forms and attributes of finished kw’éts’tel blades, explore potential slate sources, and assess decisions, techniques, and labor involved in blade production. Using an integrated methodological framework, our analyses offer nuanced insights into kw’éts’tel production and its role in Stó:lō-Coast Salish social organization. We argue that this approach enhances our ability to interpret the kw’éts’tel-focused archaeological record, shedding light on social change over time. This is particularly significant in a region where the emergence of a high-ranking social elite was partly driven by positioning and placement within the means and mode of production in the salmon-focused fishing economy.
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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 | 0.001 | 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 | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".