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From Democratization to Decolonization: Canadian Museological Theory, 1960-2000

2025· article· en· W7164053399 on OpenAlexaboutno aff
Haole Liu, Kai Yin

Bibliographic record

Venue博物院. · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsDisciplineMuseologyPoliticsDemocratizationInternational relations

Abstract

fetched live from OpenAlex

This paper examines the epistemological foundations that shaped Canadian museology in the latter half of the 20th century. Integrating distinct features of Canadian museological theory and practice across linguistic and disciplinary boundaries, it highlights scholarly ideas that have gained international resonance and influenced museum practices globally, as well as specific museological practices that have subsequently contributed to theoretical developments in the field. The 1960s marked a defining moment of radical transformation, and the paper explores how various factors—including transnational networks, reflective scholar-practitioner-activists, new cultural policies, Aboriginal activism, and the emergence of specialized academic and professional training programs—collectively influenced the development of a dynamic and innovative Canadian museological praxis. Tracing the trajectory from the late 1960s nouvelle muséologie movement's call to rethink museums' social role, through efforts to enhance public accessibility via digitization, democratization, and decentralization, to the political and moral imperative of decolonizing professional practices and institutions through reflexive, Indigenous-led, and collaborative approaches, this paper demonstrates the significant influence of both local traditions and international networks on the evolution of Canadian museological theory and practice throughout this period.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.910
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0190.000

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 head0.014
GPT teacher head0.222
Teacher spread0.208 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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