La gestion culturelle des musées au prisme du développement durable : évolution et enjeux contemporains
Bibliographic record
Abstract
Since the 2000s, the museal sector has had to face the combined challenges of sustainabilty, a fresh range of management tools coming from “new management,” and the digital revolution. While there was no real organizational disruption, several strategic behavioral patterns were observed. In fact, this changing environment brought about a progressive implementation of new tools and practises within cultural organizations. It seems important today to reevalute these organizations’ management strategies, particularly in the context of increasing globalization. First of all, there must be an awareness of research in this field to allow for the proposal of a theoretical framework that can provide the elements of comprehension of the functioning of today’s museal organizations. Analysis of the three examples of integrating a policy of sustainable development will then lead to a concrete illustration of the challenges to be met in order to conclude which contemporary issues museal management must meet today and in the future.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".