Bibliographic record
Abstract
Activities that actively and deliberately support museum visitors’ engagement with art and promote learning occupy a distinct, though contested, place in the history and current framing of the art museum across the globe. Despite its many benefits, educational work in art museums has grown erratically, frequently without formal structures, systems, or strategies, and it has been critiqued in the past for lacking a robust theoretical framework and consistent methodological principles. It remains the case that the field is broad, diverse, and continually evolving; in the early 21st century, the boundaries are shifting, for example, between what constitutes curatorial practice and learning practice in contemporary art museums. This fluidity and heterogeneity has enabled the emergence of creative and responsive practice that encourages visitors to learn with, through, and about art, but it poses challenges when the goal is to present a coherent overview. Therefore any summary of this complex domain will necessarily be selective. Nonetheless, taking the practice as it has been developed in the United Kingdom and the United States, where this work has been theorized and communicated to the greatest extent (and with reference to the practice in Europe, Canada, and Australia), it is possible to identify common historical developments, shared philosophical and pedagogical principles, and collective challenges and opportunities that contribute to a comprehensible picture, albeit one that is replete with contradictions. As a field, art-museum education continues to define itself. And although valuable research and theorization have been undertaken, in part by practitioners drawing on their own experiences, further work is required, not least to broaden the understanding of the practice as it is manifest globally and to make explicit the increasingly important role of art education within the art museum.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".