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Record W4285033062 · doi:10.36572/csm.book_07

Claims and Reality of New Museology: Case Studies in Canada, the United States and Mexico

2025· article· en· W4285033062 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsMuseologyCitizen journalismSociologyDemocracyPolitical scienceSocial scienceMedia studiesHistoryPoliticsArchaeologyLaw

Abstract

fetched live from OpenAlex

In my work, I like to go back to the source, and I love those moments when we come across historical documents that prefigure, spark or express ideas very similar to those we are developing now, with the sense of breaking new ground... Suddenly we’re not alone anymore. In fact, we’re in good company. This doctoral dissertation, originally published in 1988, could almost be considered a historical document today. I reread the opening sentence: a 1985 quote from Hugues de Varine on the museum as a perfect tool for social transformation. Decades have since gone by. New museology has become sociomuseology and various other kinds of community-oriented museologies: participative, collaborative, relational, engaged, even activist… And yet the question of the social role of museums is timelier than ever, discussed and debated at all levels of contemporary museum practice. (…) For several years now, new museology has, in its current adaptations, experienced a significant revival. In many countries, museums are exploring and practicing participatory museologies in collaboration with their communities. These approaches are part of a great and ongoing societal transformation: the creation of a true cultural democracy based on the principles of equity, diversity and inclusion. Against the backdrop of shifting cultural and power relations, many museums are developing innovative approaches not only to reflect these new realities, but to become agents of change, involved in the construction of new social imaginaries that engage a plurality of voices. How can museums do more to contribute to social and cultural justice, economic development, individual and collective well-being and a sustainable future? What real impact can they have on individuals and communities? Can they change the world? The questions that have concerned me for so long are as resonant now as they were four decades ago. I hope this text will be “good company” for today’s museum professionals. Andrea Hauenschild

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.157

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)0.0000.000

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 head0.082
GPT teacher head0.292
Teacher spread0.210 · 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.

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

Citations27
Published2025
Admission routes1
Has abstractyes

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