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Record W2797444012 · doi:10.3167/armw.2017.050116

Engaging Dialogues

2017· article· en· W2797444012 on OpenAlexaboutno aff
Silvia Forni

Bibliographic record

VenueMuseum Worlds · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeExhibitionMainstreamContext (archaeology)InstitutionMedia studiesSociologyHistoryAestheticsVisual artsPolitical scienceLiteratureArtSocial scienceLawArchaeology

Abstract

fetched live from OpenAlex

This article outlines some recent museological initiatives aimed at responding to the important issues raised by the famous protest against the exhibition Into the Heart of Africa, organized by the Royal Ontario Museum in 1989. Despite the significant temporal hiatus from the historical protest, many of the questions raised in that context continue to be relevant in thinking of ways to engage and present African collections in a mainstream encyclopedic institution. Rather than rethinking a new, more culturally sensitive narrative, I suggest that the introduction of multiple voices and perspectives may be the only way to disrupt the linear authoritative narratives and promote a more significant and affectively relevant engagement with historical collections.

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)0.009
metaresearch head score (Gemma)0.022
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 score0.029
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0120.010
Scholarly communication0.0120.011
Open science0.0020.018
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0290.006

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 head0.072
GPT teacher head0.250
Teacher spread0.177 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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