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Record W4394883282 · doi:10.26881/porta.2023.22.08

Antropologia sztuki rdzennej ludności regionu nordyckiego: reprezentacja Kalaallit Nunaat i Sápmi w muzeach skandynawskich

2023· article· en· W4394883282 on OpenAlexaboutno aff
Emiliana Konopka

Bibliographic record

VenuePorta Aurea · 2023
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousEthnohistoryEthnographyAnthropologyColonialismContext (archaeology)National museumRepresentation (politics)NarrativeHistoryAnthropology of artContemporary artSociologyArt historyArtVisual artsArchaeologyLiteraturePolitical sciencePoliticsPerformance art

Abstract

fetched live from OpenAlex

This essay is an attempt to present the most important points of the current discussion about the cultural remains of colonialism in Scandinavia by analyzing the representation of indigenous art in museums. I would like to focus on the reasons why Saami and Inuit art was usually excluded from the traditional art history narrative and placed almost exclusively in collections of ethnographic or historical museums. On the examples of the strategies applied by three museums: the National Museum of Denmark in Copenhagen, Nordic Museum in Stockholm, and the National Museum of Art, Architecture and Design in Oslo, the following issues are considered: what determines the selection of indigenous artists and their works, how they are exhibited, what place indigenous art holds in the national canon of art today, and how these museum strategies perpetuate, or not, stereotypes of Kalaallit Nunaat and Sápmi. For the sake of this paper, based on ethnohistory, historical anthropology and anthropology of art in a Nordic context, the terms ‘art’ and ‘artist’ go beyond the traditional definitions used in art history.

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)0.000
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 score0.068
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0050.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.064
GPT teacher head0.419
Teacher spread0.355 · 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
Published2023
Admission routes1
Has abstractyes

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