Creative organizations: when management fosters creative work
Bibliographic record
Abstract
Creative organizations are characterized by a tension between creative work and business. Our research mobilizes Boltanski and Thévenot’s Economies of Worth framework to explore, through the concept of compromise, how this tension is accommodated in the management of creative workers. Based on our study of eleven small advertising agencies, we identify four profiles for the management of creative work: Versatile, Creator, Manager, and Technician. Each of those profiles deals differently with the tension between creative work and business. Drawing on Boltanski and Thévenot’s framework, every profile is analyzed in terms of compromises between orders of worth, that allow the agencies to properly manage the tension. Moreover, instead of seeing management as killing creative work, we show how it can foster it. Our research contributes to the literature by developing a typology for the management of creative work that suggests four viable ways to structure creative work in advertising agencies.
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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 | 0.017 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.019 | 0.025 |
| Scholarly communication | 0.035 | 0.020 |
| Open science | 0.002 | 0.024 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".