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Record W1607415443 · doi:10.25071/1718-4657.36741

FIRST NATIONS ON VIEW: CANADIAN MUSEUMS AND HYBRID REPRESENTATIONS OF CULTURE

2005· article· en· W1607415443 on OpenAlexvenueaboutno aff
Susan L.T. Ashley

Bibliographic record

VenueIntersections conference journal · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionCONTESTColonialismRepresentation (politics)Identity (music)EthnographyRace (biology)SociologyIndigenousHistoryPoliticsMedia studiesAestheticsLawAnthropologyPolitical scienceArtArt historyGender studies

Abstract

fetched live from OpenAlex

Museums are important public sites for the representation and authentication of history and heritage in Canadian society.The study of history and ethnographic museums allows important insights into issues of race, ethnicity and identity, and especially how the colonial legacy has shaped how Canadians see themselves. Museums are a supreme expression of imperialist Europe — publicly funded institutions devoted to colonial sensibilities. This includes vast halls set up to display the “booty” of war and conquest as well as the mounds of material evidence produced by scientific research and collecting. Museums of the 19th century were concerned with objects (and objectifying) and possessed a foundational purpose to define what was cultured or civilized (and what was not). Early exhibits emphasized purity of race, the progression of history and the sense that the “white” European race was the pinnacle of evolution. Museums defined, and continue to define and present who we are as nations or communities or cultures, and inevitably separate the we from everyone else out there (Bennett, 1995; Hooper-Greenhill,1999). By using exhibition as its form of communication, museums set up frozen instances in time and fixed them, unchangeable, as expert truth; there was no opportunity then to contest or even engage in dialogue. Objects displayed, in public, for audiences to gawk at or exclaim over. This very act of exhibition was spectacular in the Debordian sense: a representation, divorced from reality, is presented to and consumed by an undifferentiated audience.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.124
Threshold uncertainty score0.899

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.008
Science and technology studies0.0390.024
Scholarly communication0.0160.008
Open science0.0020.011
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0150.000

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 head0.034
GPT teacher head0.254
Teacher spread0.220 · 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

Citations8
Published2005
Admission routes2
Has abstractyes

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