Bibliographic record
Abstract
This robust and engaging travel narrative re-creates a remarkable adventure in the summer of 1935, when Frederica de Laguna, then in her late 20s, led a party of three other scientists down the rivers of the middle and lower Yukon valley, making a geological and archaeological reconnaissance. De Laguna has based her story on her field notes, journals, and letters home. She augments this first-hand account with excerpts from the reports of earlier explorers and data published after her trip. The result is a fascinating and informative cross-cut of historical events along the Yukon River and its tributaries. Travels Among the Dena chronicles the expedition from its outfitting in Seattle and the trip by steamer and railway to Fairbanks and Nenana, through an 80-day journey on skiffs down the Tanana and Yukon rivers to Holy Cross near the coast, with side trips on the Koyukuk, Khotol, and Innoko rivers, before a one-day return flight to Fairbanks with pioneer bush pilot Noel Wien. Maps illustrate the route taken downriver, and the author’s photographs capture images of the time. The resulting volume is both a delightful addition to the literature of travel adventure in Alaska and an important contribution to the discipline of anthropology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".