A Conversation with Prof François Colbert on Arts Management
Bibliographic record
Abstract
François Colbert is among the top scholars in arts marketing in the world, having published close to 200 works and being one of the most cited authors in his discipline. He is a professor of marketing and holder of the Carmelle and Rémi Marcoux Chair in Arts Management at HEC Montréal. He founded the Master in the Management of Cultural Organizations (in French) at HEC Montréal in 1988. He created and is currently the coordinator of the joint Master of Management in International Arts Management (HEC, SMU, Bocconi). He is the Founding Editor of the International Journal of Arts Management, published by the Chair in Arts Management. He has been the UNESCO Chair in Cultural Management from 2012 to 2018. In May 2002, he was awarded the Order of Canada for his achievements and unique contributions in developing the field of arts management. He also received the Queen Elizabeth II Golden Jubilee Medal (2002) and the Queen Elizabeth II Diamond Jubilee Medal (2012). He was made a Fellow of the Royal Society of Canada in 2005. He received the ACE Award 2006 from the Association of Cultural Executives and the honorary title of “International Master” by the Chinese Ministry of Science and Technology in 2018. He is also Honorary Professor at Peking University, the National Academy of Chinese Theatre Arts, as well as at the Tianjin Conservatory of Music in China.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".