Bibliographic record
Abstract
Description from Publisher: Explorer Bruce Parry takes an epic Arctic journey, following the six-month Polar summer through Greenland, Canada, Alaska, Russia and Scandinavia to document a vital part of our world at a point of extraordinary change. In this companion to a landmark BBC series, Arctic tells the stories of traditional Arctic inhabitants along with the oilworkers, miners and scientists who have been attracted to this dramatic yet hostile landscape in search of the wealth of natural resources and ecological data it can provide. He highlights the friction between old and new ways as traditional lifestyles are threatened by many factors:climate change, new legislation and the intrusion of big business. Within engaging, intimate text and specially commissioned photography along with stills from the series, this book provides a human focus in an environmental context. Immersing himself in the cultures of peoples like the Chukchi, the Sami, the hunters of Qaanaaq and the Gwitchin tribes of the Canadian north, Bruce stresses their connection to the lands and hunting grounds that sustain them while exposing the issues they face. Rich in content and narrative, Arctic Circle with Bruce Parry brings human stories and global issues to the fore, pinpointing cultures on the brink of irreversible change.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.501 | 0.346 |
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".