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Record W7115167523 · doi:10.1080/10598650.2025.2595708

<i>my office photograph</i> as the Mapping Site for a Transformational Museum Experience

2025· article· en· W7115167523 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Museum Education · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsTransformational leadershipEthnographyTransformative learningExhibitionMuseum education

Abstract

fetched live from OpenAlex

The photographic work titled my office photograph is the mapping site for the author’s theory of a transformational museum experience centered on a situated learning methodology. Over the 14+ years of its existence, the Art Gallery of Ontario’s Artist-in-Residence program has brought numerous emerging and established artists into the daily workings of the museum, inviting resident artists to explore and engage with the museum’s collections, staff, and public programs as they develop their projects. Support for a process of research-creation is fundamental to the opportunity offered by the residency. The author, as both practicing artist and museum arts professional, has played a key role in facilitating strategies for engagement and learning in the cumulative body of residency projects and their publics. Drawing on a personal connection to the work of Heather Goodchild, one of the artists-in-residence, and situating the author’s own research-creation as a “contemplative art work and artwork” within a museum residency and laboring framework, this paper provides an account of how the involvement of artists has shaped the trajectory for a more collaborative museum engagement methodology.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.554

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.270
Teacher spread0.247 · 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 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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