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Record W4399371431 · doi:10.1017/9781009417150.005

Inuit Nunangat and the Blue Pacific

2024· book-chapter· en· W4399371431 on OpenAlexaboutno aff
Lydia Schoeppner

Bibliographic record

VenueCambridge University Press eBooks · 2024
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyGeologyOceanography

Abstract

fetched live from OpenAlex

As a result of anthropogenic climate change, Inuit in the Arctic and island inhabitants in the Pacific Ocean both experience interrelated changes in their maritime environments. Global warming causes Arctic ice to melt, which leads to rising sea levels. As a result, local inhabitants in both regions experience the disappearance of their space (land and ice), paired with the arrival of new stakeholders with a diverse range of interests in the areas. As the inhabitants of the regions most vulnerable to the effects of climate change, Inuit and Pacific Islanders have engaged in counter-mapping and counter-narrating their space that colonial powers have previously conceptualized as isolated, remote, and peripheral. In contrast, the maps of Inuit Nunangat and the Blue Pacific illustrate and tell the stories of transnational spaces that have been collectively shared and used since time immemorial. These counter-mapping and counter-narrative approaches shape a new perception of the regions. This chapter contributes to conceptual development of environmental violence by discussing case studies of counter-mapping and counter-narration in the Arctic and the Pacific Ocean – as locals’ responses to experiences of structural and cultural violence to overcome their vulnerability, challenge power differentials, and satisfy their human needs.

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 categoriesScience 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 score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.213
Teacher spread0.194 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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