Emotion in Entrepreneurship Education: Passion in Artistic Entrepreneurship Practice
Bibliographic record
Abstract
Although emotions have been recognized as fundamental for entrepreneurship and educational practices in general, the role of emotions in entrepreneurship education (EE) remains overlooked in entrepreneurship scholarship, particularly in the field of EE in the arts, where entrepreneurs are driven by their passion and strong emotional connections to their artistic projects. In this article, we discuss how emotion, and in particular passion, impacts entrepreneurship educational practices in the context of artistic entrepreneurship. Our 24-month inductive practice-based study, which used different sources of information (documents produced by the participants, direct observation, videos and semi-structured interviews) resulted in the identification of two dynamics of passion (transforming and contagious) and three aspects in which passion affected the EE process (motivation, collaboration and resilience). We conclude that our results can enrich studies in EE from different paths: discussing the relations between impacts of passion and other widely discussed constructs, broadening the understanding of passion as a dynamic and sociocultural emotion and highlighting the role of pedagogical practices in this context. Additionally, we broaden current understandings of the importance of passion for EE in the arts field.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".