MétaCan
Menu
Back to cohort
Record W4382278939 · doi:10.1515/9780773552555

Studying Arctic Fields

2017· book· en· W4382278939 on OpenAlexaboutno aff
Richard C. Powell

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2017
Typebook
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcticGeographyEnvironmental scienceComputer scienceOceanographyGeology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.870
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.274
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations10
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueMcGill-Queen's University Press eBooksSame topicArctic and Russian Policy StudiesFrench-language works237,207