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Record W2117975705 · doi:10.7202/007644ar

Uiarnerit. A historical study of immigration from East to West Greenland in the nineteenth century

2004· article· en· W2117975705 on OpenAlexvenueno aff
Einar Lund Jensen

Bibliographic record

VenueÉtudes/Inuit/Studies · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationSettlement (finance)GeographyEthnologyPopulationHistoryColonialismConsciousnessPolitical scienceArchaeologyDemographySociology

Abstract

fetched live from OpenAlex

This article is about 50 East Greenlanders who settled in the Kap Farvel area in 1887, and about their encounter with the local population, the German Moravian Brethren mission, and the Danish mission and colonial administration. On the basis of this immigration, the article gives an account of a number of new issues and perspectives on settlement and the settlement policy for the overall immigration from East Greenland to South West Greenland and the traces left by these migrations on South West Greenland right up to now. Despite formal status as West Greenlanders, the immigrants and their descendants preserved East Greenlandic features which in many ways still exist, and today people in the area take a great deal of interest in the historical events, the distinctive features of the immigrants and their links with East Greenland. One motive for this study is thus a growing local wish to turn the focus on the migrations from East Greenland and to raise consciousness about their significance for the present-day situation. The following account is intended as a contribution to this consciousness-raising process. The article presents a hitherto unexploited body of historical and ethnohistorical sources which will be used as the basis for a future historical study of the immigration from East Greenland to West Greenland and to improve our knowledge of the cultural, social and other traces of East Greenlanders in South West Greenland, and how these traces were kept.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.789
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.060
GPT teacher head0.341
Teacher spread0.282 · 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.

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

Citations1
Published2004
Admission routes1
Has abstractyes

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