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Record W4379352461 · doi:10.32873/unl.dc.zea.1406

Las complejidades de colecciones históricas de Latinoamérica en museos europeos: casos de colecciones controvertidas y su seguimiento

2023· article· es· W4379352461 on OpenAlexaff
Alexander Brust, Manuela Fischer, Adriana Muñoz

Bibliographic record

VenueZea Books · 2023
Typearticle
Languagees
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

El presente trabajo muestra el panorama multifacético de colecciones clasificadas como etnográficas y que son controvertidas por sus contextos de adquisición y adscripciones alternativas en el trascurso del tiempo. El estudio se centra en cinco casos del Museo de las Culturas de Basilea (Suiza) del Museo Etnológico en Berlín (Alemania) y de los Museos Nacionales de la Cultura del Mundo en Gotemburgo, (Suecia) que los autores han acompañado de cerca en los últimos años y que involucran procesos de restitución. El trabajo esboza la complejidad de las visiones acerca del «objeto etnográfico» y muestra la importancia de entender las agendas de los actores involucrados –como instituciones privadas y estatales, representantes de comunidades indígenas, ONGs y particulares– en diferentes fases de los procesos, que a la vez suelen ser marcadas por cambios en las políticas patrimoniales, cambios de gobiernos y alianzas. El presente ensayo es una invitación a reflexionar profundamente sobre los contextos actuales, las intenciones y los trasfondos de pedidos de restitución.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0100.015
Scholarly communication0.0090.004
Open science0.0010.007
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.260
Teacher spread0.228 · 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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