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Record W7072241690

Transformative Opportunities through Decolonizing and Indigenizing Museums: People, Collections, Exhibitions

2022· dissertation· en· W7072241690 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2022
Typedissertation
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionIndigenousEthosPower (physics)MuseologyColonialismStorytellingAside
DOInot available

Abstract

fetched live from OpenAlex

The postponement of a new definition for the word museum at the International Council of Museums conference in September 2019, along with growing societal interest and attention to museums, memory institutions, and heritage spaces as locations for decolonizing opportunities, suggests that the first quarter of the 21st century has unsettled aspects of our world that were formerly taken for granted by some. Museums’ inheritance from past generations of assumed authority is being critically evaluated from multiple perspectives. Yet within the profession, aside from inclusive gestures like sharing authority for exhibition content about Indigenous topics with Indigenous experts, some museum staff, policies, and procedures remain firmly embedded in an ethos of colonial entitlement. In what is now known as Canada, the worldviews of white, Euro-descended, settler populations tend to be presented as the norm, or assumed to be the perspective from which museum texts are written and consumed. This default position relies on the mistaken assumption that Euro-centric, Enlightenment-era worldviews, behaviours, and tendencies are the only ways through which the world can be observed, named, and ordered. As I demonstrate throughout this thesis, these beliefs foreclose upon and erase other possibilities of seeing, being, and living-in-relation with. My research presents decolonizing and Indigenizing approaches to ways of being and working in museums primarily for settler museum professionals; a case study of concealed power and authority in a museum using semi-structured community-based research interviews; and, aspirational imaginings of a geology museum in decolonizing and Indigenizing futures.

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)0.004
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: Other · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0290.074
Scholarly communication0.0120.009
Open science0.0020.021
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.024
GPT teacher head0.201
Teacher spread0.178 · 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
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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