Bibliographic record
Abstract
Museums throughout the world are under increasing pressure in the wake of the 2008/2009 economic recession and the many pressing social and environmental issues that are assuming priority. The major focus of concern in the global museum community is the sustainability of museums in light of these pressures, not to mention falling attendance and the challenges of the digital world. Museums and the Paradox of Change provides a detailed account of how a major Canadian museum suffered a 40 percent loss in its operating budget and went on to become the most financially self-sufficient of the ten largest museums in Canada. This book is the most detailed case study of its kind and is indispensable for students and practitioners alike. It is also the most incisive published account of organizational change within a museum, in part because it is honest, open and reflexive. Janes is the first to bring perspectives drawn from complexity science into the discussion of organizational change in museums and he introduces the key concepts of complexity, uncertainty, nonlinearity, emergence, chaos and paradox. This revised and expanded third edition also includes new writing on strengthening museum management, as well as reflections on new opportunities and hazards for museums. It concludes with six ethical responsibilities for museum leaders and managers to consider. Janes provides pragmatic solutions grounded in a theoretical context, and highlights important issues in the management of museums that cannot be ignored.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.025 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| 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".