Innover en facilitant l'appropriation critique des technologies par le design thinking : le cas de PRISME, laboratoire d'innovation numérique du Musée des beaux-arts de Montréal
Bibliographic record
Abstract
This article explores the evolution of management models in museums, focusing on the adoption of design thinking as a method for managing innovation in the digital age. It examines the PRISME digital innovation laboratory at the Montreal Museum of Fine Arts through a qualitative investigation, including interviews and observations. The study identifies tensions between design thinking principles and traditional museum organizational values, while highlighting the contributions of this approach to organizational culture, such as collaboration, risk tolerance and learning by doing. The design thinking approach, which takes place over a long period of time (several months with the same participants), is appreciated for its ability to encourage critical reflection on the impact of projects before they are carried out. The article invites us to consider design thinking as a tool for critical appropriation of technologies, especially in the current context of socio-ecological crisis.
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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 | 0.019 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.049 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| 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".