An Anthropologist’s Apprenticeship: Diamond Jenness’ Papuan and Arctic Fieldwork
Bibliographic record
Abstract
Diamond Jenness (1886-1969) was a major figure in Canadian anthropology during the first half of the century. This paper provides some biographical-historical details of his early career, concentrating on major fieldwork in Papua New Guinea in 1912, and in northern Alaska and Canada’s Coronation Gulf region between 1913 and 1916. Relying mainly on Jenness’ unpublished field diaries and personal correspondence, it identifies links between his work in the south Pacific and the Arctic, and examines the source of prominent themes that found expression during his later professional career. Particular attention is given to the three years Jenness served as a member of Stefansson’s Canadian Arctic Expedition, and to his role in accomplishing the Expedition’s anthropological objectives.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".