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ćəsnaɁəm, the City before the City: exhibiting pre-Indigenous belonging in Vancouver

2019· book-chapter· en· W2945993469 on OpenAlexaboutno aff
Paul Tapsell

Bibliographic record

VenueManchester University Press eBooks · 2019
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionEphemeral keyIndigenousVisitor patternMedia studiesVisual artsSociologyGeographyAnthropologyHistoryGenealogyArt historyArt

Abstract

fetched live from OpenAlex

ćəsnaɁəm, the city before the city is a boundary-breaking exhibition that has successfully challenged the museum world to revisit who is the curator and who is the audience. This chapter provides an indigenous-framed insight into kin accountability as (re)presented to the museum world from the local tribal/aboriginal community perspective of Musqueam. The exhibition was simultaneously displayed in three venues of the Vancouver city region, each providing multiple perspectives of the original inhabitants of a village named c̓əsnaʔəm more than 5000 years old. While the central city venue at the Museum of Vancouver was high-tech and pitched to an international museum visitor, the Museum of Anthropology exhibit was uniquely ephemeral, transient and aimed at shifting preconceived perceptions of what it means to be a modern aboriginal raised in a city established on thousands of years of unbroken occupation. The most challenging of the three exhibits was to be found in the Musqueam village Culture Centre. In this instance the art and treasures were displayed in a manner that required elders to provide interpretation and the audience is their own. Three exhibits, three boundary breaking contact zones, one people, Musqueam.

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.215
Threshold uncertainty score0.433

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.004
Scholarly communication0.0060.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.032
GPT teacher head0.187
Teacher spread0.155 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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