Making Fun of the Museum: Multidisciplinarity, Holism, and 'The Return of Curiosity'
Bibliographic record
Abstract
Museums are curious institutions in two senses, one arising from the eccentricities and peculiarities of their histories, and the other from their ongoing desire to display, provoke, and satisfy their visitors' curiosity about the world in which they live. As the critical literature has shown, we can think about Western museums as material deposits of the different forms curiosity has taken in the course of four centuries of European imperial expansion and colonial domination - as sites where the properties of things could be disciplined according to Western knowledge structures and deployed to create a comprehensive picture of the world. Although this consciousness has shaken the foundations of museums and dislodged the collections they hold, their value as places where colonial legacies can be negotiatied and shared concerns addressed remains compelling. Responding to Nicholas Thomas's The Return of Curiosity, to Actor-Network-Theory's insistence on connecting disciplinary knowledges, and to Indigenous reaffirmations of holistic knowledge formation, this article explores a range of recent museum projects that invoke curiosity to transgress the museum's modern disciplinary boundaries.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.087 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".