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Inuit landscape use and responses to climate change in the Wollaston Forland—Clavering Ø region, Northeast Greenland

2010· article· en· W2314956730 on OpenAlexaboutno aff
Mikkel Sørensen

Bibliographic record

VenueGeografisk Tidsskrift-Danish Journal of Geography · 2010
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsGeographyArcticFjordPhysical geographyPrehistorySettlement (finance)Circumpolar starDanishClimate changeOceanographyArchaeologyGeology

Abstract

fetched live from OpenAlex

Geografisk Tidsskrift—Danish Journal of Geography 110(2):155–174, 2010 The Thule culture of the Wollaston-Clavering Ø area is analysed and their settlement pattern as recorded within the area is presented and analysed in relation to the following high arctic seasons: winter, spring and summer. From the analysis it is seen that a defined and stable seasonal mobility between coast, fjords and inland existed and that the “Sirius Water Polynya” off Wollaston Forland and Sabine Ø, holds the key to understanding the human economy and settlement patterns in the research area, as well as in the region. The cooling of the Little Ice Age, interpreted from the analysed data, does not affect the Inuit exploitation of the research area or their material culture in general. The main Inuit response to the cooling is migration, a response that can only be analysed when Northeast Greenland is studied regionally and interregionally. As migration is defined as an important part of prehistoric ‘Inuit being’, the Inuit made no additional strategies or inventions during the LIA. Inuit migration is, in this way, demonstrated to be a substantial contributor to the Inuit's cultural resilience and to their long-term existence in the Arctic.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.032
GPT teacher head0.320
Teacher spread0.288 · 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 designObservational
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

Citations12
Published2010
Admission routes1
Has abstractyes

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