Bibliographic record
Abstract
In 2017, thirty years after Lenny Kohm first visited the Arctic, Lorraine Netro organized a caribou dinner and screening of The Last Great Wilderness slide show in the community hall in Old Crow, Yukon. This chapter describes how Vuntut Gwitchin responded to the show. Their questions afterwards addressed issues ranging from climate change to alliance-building with environmentalists and the role of Vuntut Gwitchin in the Arctic Refuge struggle. They also asked what happened to Kohm’s other photographs (not just those in the slide show) taken in and around Old Crow. Delving into the questions they posed, the chapter highlights how particular photographs—including Kohm’s at Norma Kassi’s family hunting camp along Zelma Lake and Subhankar Banerjee’s of polar bear denning sites along Beaufort Sea—can be seen as historic records of Arctic lands before they were so dramatically impacted by catastrophic climate change. Finally, the chapter explains how the author eventually found Kohm’s other Arctic slides and had them digitized and returned to the Vuntut Gwitchin First Nation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.058 | 0.009 |
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".