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Record W1977347492 · doi:10.1080/09647770903073060

Museum experiences that change visitors

2009· article· en· W1977347492 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMuseum Management and Curatorship · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsUniversity of Toronto
FundersAga Khan Foundation Canada
KeywordsExhibitionTransformational leadershipTransformative learningMuseologySociologyVisual artsPublic relationsPolitical scienceArtPedagogy

Abstract

fetched live from OpenAlex

Abstract Transform, transforming, and transformative are common terms for describing museum spaces, the creation of objects on display, and experiences for visitors. But is there evidence that museums profoundly change visitors through their objects, collections, exhibitions, public programs, and websites? The nature of transformational museum experiences and potential ‘triggers for transformation’ are the focus of this article. Two case studies describe ways in which visitors articulate change they have experienced. Included are projects about teachers and artists during an intense two-week summer institute in an interdisciplinary museum and about visitors to a traveling exhibition highlighting the role Canada plays in international development. Individuals’ comments and questions indicated that experiences with authentic objects and the unexpected, highly emotional responses, new cultural and attitudinal understandings, as well as motivation to become more proactive in the way they live their lives, may have been triggers for transformational experiences.

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.

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: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.999

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.091
GPT teacher head0.236
Teacher spread0.146 · 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