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Record W3203323627 · doi:10.1111/oli.12329

Growing into epistemic knowledge through performance: Rosanna Raymond’s “Soli I Tai—Soli I Uta” at Berlin’s Ethnological Museum

2021· article· en· W3203323627 on OpenAlexaboutno aff
Torsten Jost

Bibliographic record

VenueOrbis Litterarum · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsPerformative utteranceAotearoaSociologyIntervention (counseling)AestheticsArtPsychologyGender studies

Abstract

fetched live from OpenAlex

Abstract This article explores Rosanna Raymond’s performative intervention titled “Soli I Tai—Soli I Uta” (Tread on the Sea—Tread on the Land). Today, many cultural institutions try to develop progressive strategies to facilitate “intercultural dialogue.” In this endeavor, performative strategies are explored, some of which are developed in collaboration with experts from so‐called “source communities.” Such collaborations have longer histories in Australia, Aotearoa New Zealand, or Canada. In central Europe, and especially in Germany, this has been a more recent development. One prominent example is the one‐month artist residency of the Pacific artist Rosanna Raymond (b. 1967) at the Ethnological Museum Berlin in 2014, which culminated in her “acti.VA.tion” entitled “Soli I Tai—Soli I Uta.” My article analyzes how Raymond’s performative intervention dramaturgically put different epistemic systems and “ways of knowing” into a contrasting relationship and thus enabled spectators to gain declarative epistemic knowledge, that is to say, knowledge about knowledge and different “ways of knowing.”

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)0.005
metaresearch head score (Gemma)0.005
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 score0.033
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0330.029
Scholarly communication0.0090.005
Open science0.0020.013
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0100.001

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 head0.040
GPT teacher head0.339
Teacher spread0.299 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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