Bibliographic record
Abstract
In recent years the circumpolar region has emerged as the key to understanding global climate change. The plight of the polar bear, resource extraction debates, indigenous self-determination, and competing definitions of sovereignty among Arctic nation-states have brought the northernmost part of the planet to the forefront of public consideration. Yet little is reported about the social world of environmental scientists in the Arctic. What happens at the isolated sites where experts seek to answer the most pressing questions facing the future of humanity? Portraying the social lives of scientists at Resolute in Nunavut and their interactions with logistical staff and Inuit, Richard Powell demonstrates that the scientific community is structured along power differentials in response to gender, class, and race. To explain these social dynamics the author examines the history and vision of the Government of Canada’s Polar Continental Shelf Program and John Diefenbaker’s “Northern Vision,” combining ethnography with wider discourses on nationalism, identity, and the postwar evolution of scientific sovereignty in the high Arctic. By revealing an expanded understanding of the scientific life as it relates to politics, history, and cultures, Studying Arctic Fields articulates a new theory of field research. Advocating for a greater appreciation of science in the remote parts of the world, Studying Arctic Fields is an innovative approach to anthropology, environmental inquiry, and geography, and a landmark statement on Arctic science as a social practice.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".