Making Science Accessible to Inuit, Inughuit, and Iñupiat Arctic Indigenous Communities in Their Own Languages; Qaanaaq, Greenland; Barrow, Alaska; Clyde River, Nunavut, Canada; 2013-2017
Bibliographic record
Abstract
The Meaning of Ice celebrates Arctic sea ice as it is seen and experienced by the Inuit, Iñupiat, and Inughuit, who for generations have lived with it and thrived on what it offers. With extensive details offered through their own drawings and writings, this book describes the great depth of Inuit, Iñupiat, and Inughuit knowledge of sea ice and the critical and complex role it plays in their relationships with their environment and with one another. Over forty Inuit, Iñupiat, and Inughuit from three different Arctic communities contributed stories, original artwork, hand-drawn illustrations, maps, family photos, and even recipes to this book. Professional and historical photographs, children's artwork, and innovative graphics add more to the story of The Meaning of Ice. The Meaning of Ice is an important contribution to understanding the Arctic and its people at a time when the region is undergoing profound change, not least in terms of sea ice. It takes readers beyond what sea ice is, to broaden our appreciation of what sea ice means.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.032 |
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".