Bibliographic record
Abstract
From the 16th to 18th centuries, Labrador Inuit seem to have valued softwoods (from coniferous tree boles) for the manufacture of arrows and darts used in hunting and warfare. Microscopic examination of Inuit arrow shafts from the Twin Island 3 site (EkBc-07) in Red Bay shows that balsam fir (Abies balsamea) was the preferred species for these purposes in the 16th century. Balsam fir is found in abundance in the inner bays of southern Labrador and was easily accessible to Inuit. However, archival sources indicate that by the 18th century Labrador Inuit desired another species of softwood for arrow and dart shafts, one that grew only on the island of Newfoundland. I propose that the sought-after species was one, or both, of the two pine species growing in central Newfoundland (Pinus strobusorPinus resinosa).Procurement of pine wood from Newfoundland would add another dimension to the established mobility and trading patterns of Inuit in southern Labrador. Conflicts with Europeans during the 16th through 18th centuries in the Strait of Belle Isle and the Petit Nord (on Newfoundland’s Great Northern Peninsula) may, in part, have been a result of the disruption in these travel and harvesting patterns. I suggest that iron products and wooden shallops (boats) from southern Labrador and northern Newfoundland were not the only “southern” commodities actively sought by Inuit during the early stages of European occupation; central Newfoundland’s pine wood was also important for manufacture of arrow shafts.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".