Bibliographic record
Abstract
The role of art museum educators has shifted from presenter of information to facilitator of dialogue. But as art museums pledge to be more accountable to — and representative of — a plurality of publics and narratives, what is spoken about with visitors? Given revolving temporary exhibitions and expanded readings of permanent collections, guides play a dual role of adult learner and educator. This article asks what learning opportunities equip art museum guides to critically engage with challenging subject matter. A qualitative research project grounded in the author’s reflective practice, it draws on interviews with newly trained volunteer guides. Responses suggest that guides’ relationships to challenging subject matter are multilayered and deserving of both personal and institutional attention. Findings point to a need for support that includes, but is not limited to, ongoing training. This article will contribute to the growing but limited scholarship on art museum educators’ learning, speaking to efforts by trainers and adult educators to foster reflexivity and critically embrace the potentially challenging and necessary dialogues inspired by art museum collections.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".