Exploring Creative Spaces Predict Domain‐Specific Creative Achievements
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT This study aimed to understand the factors predicting creative activities and creative achievements among university students. Based on a recently proposed framework of 10 creative spaces, we hypothesized that exploring those creative spaces, alongside the personality trait openness to experience and divergent thinking abilities would predict creative activities and achievements in specific domains. Using the Inventory of Creative Activities and Achievements (ICAA) to evaluate eight domains of creativity, two divergent thinking tasks, and one associative task, we analyzed a sample of n = 300 university students. The results of Structural Equation Models revealed that the creative spaces significantly predicted creative activities and creative achievements in the eight domains assessed. The model explained in average 27% of the variance in creative activities and 17% in creative achievements. Openness significantly predicted creative activities in music, literature, and arts and crafts. Intellect did not significantly predict any domain. Lastly, fluency in divergent thinking was positively associated with all domains (average coefficient of β = .15), despite not always reaching significance. We discuss the roles of the recently proposed creative spaces, as well as openness to experience, and fluency in predicting creativity across various domains.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it