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Record W2913941553 · doi:10.3167/sib.2018.170102

Vilhjalmur Stefansson

2018· article· sv· W2913941553 on OpenAlexaboutno aff
Paul Dukes

Bibliographic record

VenueSibirica · 2018
Typearticle
Languagesv
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEmpireContext (archaeology)Soviet unionHistoryAdventureArcticThe arcticAncient historyPeriod (music)ArchaeologyPolitical scienceLawGeologyArtArt historyOceanographyPolitics

Abstract

fetched live from OpenAlex

Vilhjalmur Stefansson was an Arctic explorer and anthropologist. The article analyzes two of his books, The Northward Course of Empire and The Adventure of Wrangel Island, in the context of the “universal revolution” including World War I and the Russian Revolution at a time when Siberia, especially its Arctic region, was widely seen as separate from the rest of the former Russian Empire. Stefansson moved through the English-speaking world of Canada, the US, and Great Britain, while acting as an advocate of the colonization of the Arctic region. Later, Stefansson’s connections with the Soviet Union put him under suspicion of un-American activities, but a retrospective assessment of his career shows him to be a sometimes mistaken but often farsighted advocate of Arctic development.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0430.027

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 head0.353
Teacher spread0.315 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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