Entrepreneurial Competencies in the Creative Industry: A Study with Music Professionals
Bibliographic record
Abstract
Despite the importance of the creative industry for the economy and the need for entrepreneurship education in this area (DCMS, 2001; UNESCO, 2013), there is still a limited understanding of the content and methods to be used in teaching entrepreneurship to creative industry professionals (Damásio & Bicacro, 2017; Matetskaya, 2015). The present research aims to understand the needs and ways of learning of creative industry professionals, regarding the development of their entrepreneurial competences. Semi-structured interviews were conducted with 31 Brazilian musicians who have their own businesses. The results indicate that most musicians learn best through practice, searching for information and learning contents on Youtube and face difficulties to concentrate while learning. Regarding the learning needs of entrepreneurial competences, management skills, especially time management and organization, stand out. The article contributes to the understanding of entrepreneurial competences and learning in the creative industry. It brings evidence about the learning process of creative professionals (musicians) and reveals main development needs of entrepreneurial competences in this context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".