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Record W2101242336 · doi:10.7202/1028853ar

Greenlandic attitudes towards Norwegians and Danes from Nansen’s icecap crossing to the 1933 World Court verdict in The Hague

2015· article· en· W2101242336 on OpenAlexvenueno aff
Karen Langgård

Bibliographic record

VenueÉtudes/Inuit/Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNorwegianDanishNegotiationColonialismPower (physics)NewspaperSettlement (finance)VerdictWelshPolitical scienceEthnologyHistoryGeographyCriminologyGender studiesSociologyLawArchaeology

Abstract

fetched live from OpenAlex

After Fridtjof Nansen (1861-1930) crossed the Greenland icecap, he spent the winter in Nuuk and impressed the Greenlanders not only by demonstrating his skill and daring in kayaking, but also by his openness to Greenlandic food, culture, and traditions. Later on, when Danes and Norwegians came into conflict over Greenland, Greenlanders supported the Danish colonial power against Norway, while at the same criticizing the Danes for not paying enough respect to Greenlanders during the process. Articles from the national Greenlandic newspapersAtuagagdliutitandAvangnâmioĸdemonstrate that Greenlanders were open-minded towards Norwegians but critical towards Danes. They fully supported the latter as a colonial power against Norway, while never refraining from the idea that Greenland remained their ethnic-national territory, even though for the time being it was colonized by the Danes. The author concludes that Greenlandic agency found in these newspapers is very relevant when negotiating today’s discourse on colonial Greenlanders.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.728

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.013
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.124
GPT teacher head0.396
Teacher spread0.272 · 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 designQualitative
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

Citations4
Published2015
Admission routes1
Has abstractyes

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