Caribou Hunting at Mingo Lake: A Comparative Study of Pre-Dorset and Late Dorset Hunting Methods
Bibliographic record
Abstract
Caribou are a very important resource in the Arctic because they provide food, raw material for weapons and tools and skins for warm winter clothing. The methods used to hunt these animals have been studied extensively by ethnographers who lived with and observed Inuit groups during the late 19th and early 20th century. At that time, hunting methods were changing due to the fur trade and the introduction of rifles but there were still groups who used older methods of hunting that would have been similar to techniques used by ancient arctic peoples. LdFa-1 is a multi-component caribou-hunting site on the northwestern corner of Mingo Lake, Southern Baffin Island, Nunavut that was used by the Pre-Dorset, Dorset, Thule, and Inuit. The focus of this paper is the distinct Pre-Dorset and Late Dorset occupations. The Pre-Dorset lived from around 4,500 B.P. to 2,700 B.P. before developing into the technologically different Dorset culture, who survived until sometime before 700 B.P. before disappearing for reasons that are still unclear to archaeologists. The Pre-Dorset and the Late Dorset both hunted caribou at Mingo Lake but the only surviving evidence for the methods they used are in the form of a few stone endblades and harpoon heads. Due to this limited archaeological evidence, a study that combines ethnographic accounts with the archaeological data has the potential to determine which techniques for hunting caribou at Mingo Lake would have been possible by each culture with the technology it possessed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".