Dorset Harpoon Endblade Hafting and Early Metal Use in the North American Arctic
Bibliographic record
Abstract
Composite tool hafting research has touched upon almost every era and region of human history. One aspect that has seen little attention is how those traces of hafting strategies might reflect the raw material of the endblade that an organic handle would have held. This aspect is particularly important for clarifying the scope and scale of novel raw material use in contexts that have concurrent use of different lithic, bone, and metal materials. This article analyzes harpoon heads from the Canadian Arctic in Dorset cultural contexts and identifies three different hafting techniques employed across time. For roughly one millennium, Dorset groups used a single harpoon endblade hafting technique. After AD 500, new hafting techniques were developed, corresponding with the emergence of metal use. Some of these methods are not compatible with common chipped stone materials and signal an increase in metal endblade production. However, surviving metal objects are underrepresented in museum collections because of various taphonomic processes. By recognizing the materials of the harpoon endblade and the specific constraints of some hafting techniques, it is possible to identify what these endblade materials may have been and expand the known extent and intensity of early metal use by observing the hafts alone.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".