A Successful Creative Process: The Role of Passion and Emotions
Bibliographic record
Abstract
The creative process refers a sequence of thoughts and actions leading to a novel, adaptive production (Lubart, 2000 Lubart, T. I. (2000). Models of creative process: Past, present, and future. Creativity Research Journal, 13, 295–308.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). It demands love, time, and devotion, and, therefore, creators are passionate toward their creative work. The Dualistic Model of Passion (Vallerand et al., 2003 Vallerand, R. J., Blanchard, C., Mageau, G. A., Koestner, R., Ratelle, C. F., Léonard, M., … Marsolais, J. (2003). Les passions de l'âme: On obsessive and harmonious passion. Journal of Personality and Social Psychology, 85, 756–767.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) defines passion as a strong inclination for a self-defining activity that people love and find important, and in which they invest a significant amount of time and energy. Two types of passion are proposed, where harmoniously passionate (HP) individuals engage in the passionate activity with free choice, and obsessively passionate (OP) individuals feel an uncontrollable urge to partake in the activity, leading to positive and negative consequences respectively. This research explored the role of emotions and passion during a successful creative process. Study 1 (N = 82) looked at positive emotions experienced by passionate artists at each phase of their creative process. Study 2 (N = 114) replicated Study 1 and also assessed negative emotions. Results revealed that positive emotions facilitate creativity and that moderate and high levels of activation of positive emotions serve different functions. Negative emotions were relatively absent of the successful creative process. Finally, HP artists presented an emotional experience that was more positive than OP artists.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| 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".