Screen Size and the Need for Reinterpretation: A Case Study from the Northwest Coast
Bibliographic record
Abstract
There has been much discussion in the archaeological literature on the utilization of different screen mesh sizes for recovering faunal elements, with many researchers decrying the use of the 6.4 mm (1/4") screen, which allows small elements to fall through the mesh. There has been less discussion on the merits of the data obtained through recovery of smaller elements, specifically, is the "new data" worth the extra time and labor? This paper examines faunal material from three sites from the Northwest coast of Canada. The material has been recovered using either 6.4 mm or 2.8 mm (1/8") mesh screens. The results suggest that elements of herring and other small fish have been greatly underestimated in Northwest coast sites, and that these formed an important part of the coast economy and subsistence. Where salmon, a large fish with often well preserved elements, has been seen as the mainstay of Northwest diet and economy, excavation with small-mesh screens may indicate a much greater importance for herring and other small fish on the coast. For accurate reconstruction of past lifeways, at least on the Northwest coast, screens with mesh 2.8 mm must be used for at least a substantial part of the matrix, in combination with the 6.8 mm mesh.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".