The hybrid exhibits of the story museum: The child as creative artist and the limits to hands-on participation
Bibliographic record
Abstract
Since the Brooklyn Children’s Museum opened in 1899, the concept of the children’s museum has evolved internationally as a non-profit public institution focused on informal family-centred education and interactive play environments (Acosta 2000; Allen 2004). The majority of these museums highlight science education; however, over the past decade, a new specialized institution has emerged in the form of the children’s story museum that concentrates on children’s literature, storytelling, and picture book illustration. These story museums feature childhood artifacts through the curatorial and display conventions of museums and art galleries, in combination with the active play environments and learning stations of science-oriented children’s museums. These exhibits also reflect the changing place of the museum as an institution in the age of the “participatory museum”: a movement away from collections towards interactive curatorial practices across physical and digital archives (Simon 2010; Janes 2011). Framed by cross-disciplinary theoretical and methodological approaches from critical children’s museology, picture book theory, and children’s culture studies, this analysis draws upon selected examples (2014-2018) of curatorial practices, exhibits, and the spatial/ architectural design from Seven Stories: National Centre for Children’s Books (Newcastle, UK), the Hans Christian Andersen Haus/Tinderbox (Odense, Denmark), and The Eric Carle Museum of Picture Book Art (Amherst, MA, USA). These institutions provide distinctive venues to examine the tensions between discourses of museums as institutions that house collections of material artifacts including children’s literature texts, discourses of the creative child and ‘hands-on’ engagement (Ogata 2013); and discourses of critical engagement and participatory museums. While these exhibits affirm idealized representations of childhood to some extent, participatory engagements across old and new media within these spaces have significant potential for critical and subversive dialogue with ideological constructions and representations of gender, race, socio-economic class, mobility and nationalism rooted in the children’s literature texts.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.033 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".