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Record W4237404755 · doi:10.4324/9781315743844

Climate, Society and Subsurface Politics in Greenland

2017· book· en· W4237404755 on OpenAlexaff
Mark Nuttall

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPoliticsPolitical scienceGeographyEnvironmental scienceClimatologyGeologyLaw

Abstract

fetched live from OpenAlex

Once imagined as a place on the very edge of the world, Greenland is now viewed as being at the epicentre of climate change. At the same time, international attention is focused on opportunities for oil and mineral development, seemingly made possible as the inland ice melts and sea ice disappears, revealing geological riches and making access to remote areas easier. In this book, Mark Nuttall takes the reader on a journey through landscapes, seascapes and icescapes of memory, movement and anticipation. Unravelling the entanglements of climate change, indigenous sovereignty and the politics surrounding non-renewable resource extraction, he describes how the country is on the verge of major environmental, political and social transformations as it aspires to greater autonomy and possible independence from Denmark. At the heart of this is discussion about how resources and the environment are given meaning and how they have become subject to intense political and ideological struggle. Climate, Society and Subsurface Politics in Greenland: Under the Great Ice is a key resource for academics, practitioners and students of anthropology, geography, development studies, political ecology and polar studies.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.005
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.331
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations36
Published2017
Admission routes1
Has abstractyes

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