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Record W4415620805 · doi:10.7202/1120378ar

Education of Avanersuarmiut, the Northernmost People in Qaanaaq

2024· article· fr· W4415620805 on OpenAlexvenueno aff
Naja Blytmann Trondhjem

Bibliographic record

VenueÉtudes/Inuit/Studies · 2024
Typearticle
Languagefr
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsDanishPerspective (graphical)Stigma (botany)Colonialism

Abstract

fetched live from OpenAlex

This paper describes how the concept of centre-periphery is linked to modernity, and thus to colonialism and coloniality, by examining the education of non-Kalaallisut-speaking Avanersuarmiut children in Qaanaaq through teaching materials, national tests, and final exams in Kalaallisut, Danish, and English. Within coloniality, the multidialectal perspective is not considered relevant, and the emphasis on the standard language marginalizes local dialects to near extinction. Despite linguistic challenges at the start of schooling, children in Qaanaaq eventually achieve scores comparable to those of Kalaallisut-speaking children. However, due to limited exposure to Danish and English, they obtain low scores in these subjects. When they move to other parts of Greenland for further education, they struggle not only with Danish and English but also with Kalaallisut, facing stigma because of their accent. Despite these challenges, many persevere, supported by second-chance programs that help them eventually complete their education.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.186
Threshold uncertainty score0.371

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.061
GPT teacher head0.420
Teacher spread0.359 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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