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Record W2167142449 · doi:10.1353/arc.0.0027

Blessings and Horrors of the Interior: Ethno-Historical Studies of Inuit Perceptions Concerning the Inland Region of West Greenland

2009· article· en· W2167142449 on OpenAlexaboutno aff
Bjarne Grønnow

Bibliographic record

VenueArctic Anthropology · 2009
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyCreaturesArchaeologyHistoryFishingNatural (archaeology)Fishery

Abstract

fetched live from OpenAlex

The yearly cycle of the marine adapted historic Inuit in western Greenland included a stay in Nunap Timaa, the Inland (or interior), where they hunted on the high plains bordering the inland ice. Families traveled far to reach the “classical” hunting grounds, where they spent a few weeks in summer camps hunting caribou and fishing for char. Summer was a great time for feasting and socializing. At the same time, however, the inland region was considered extremely dangerous: it was haunted by qivittut [human outcasts] and a great variety of “non-empirical” creatures: ghosts, inland people, giants, animal monsters, etc. These inland beings are presented in a comprehensive database on legends and tales from nineteenth century western Greenland. Inuit had contradictory feelings about the Inland and the Greenland Ice Cap, which were perceived as a dangerous transitional zone between worlds, yet these landscapes held an important position in the view of the world of historic Inuit.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.272
Threshold uncertainty score0.540

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0120.009
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.091
GPT teacher head0.410
Teacher spread0.319 · 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

Citations8
Published2009
Admission routes1
Has abstractyes

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