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Record W2098816671 · doi:10.7202/1025258ar

Jørgen Meldgaard’s film works and books on art from the Arctic

2014· article· fr· W2098816671 on OpenAlexvenueaboutno aff
Anne Mette Jørgensen

Bibliographic record

VenueÉtudes/Inuit/Studies · 2014
Typearticle
Languagefr
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPassionArt historyPsychology

Abstract

fetched live from OpenAlex

L’archéologue danois Jørgen Meldgaard (1927-2007) était un cinéaste passionné. Les archéologues d’aujourd’hui pourraient s’inspirer de sa passion pour ce médium qu’est le film. Il a produit trois documentaires incontournables au cours de sa carrière, chacun d’eux illustrant une tendance importante de la représentation scientifique de l’Autre durant la seconde partie du XXe siècle. Cet article analyse ses films en portant une attention particulière à la manière dont Meldgaard est passé d’une représentation des Inuit en tant qu’objets à une représentation en tant que sujets. Il effectue également une comparaison de ses films avec ses deux ouvrages sur l’art inuit et les replace dans le contexte des développements méthodologiques contemporains en archéologie et en anthropologie. Il conclut en recommandant aux futurs archéologues de suivre l’exemple de Meldgaard en s’engageant dans le partage de la connaissance, par l’intermédiaire des médias audiovisuels, avec les gens concernés par les fouilles archéologiques, plutôt que de laisser entièrement la représentation de la connaissance archéologique aux professionnels des médias.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.120
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.003
Scholarly communication0.0070.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.058
GPT teacher head0.260
Teacher spread0.202 · 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 designNot applicable
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
Published2014
Admission routes2
Has abstractyes

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