Interview: <scp>P</scp>aul <scp>P</scp>aulus on Group Creativity
Bibliographic record
Abstract
Paul Paulus is Distinguished Professor of Psychology at the Department of Psychology, University of Texas at Arlington. Paul Paulus's research interests revolve around Group Creativity: On the one hand, creative processes are often conceptualized as individual‐level phenomena. On the other hand, complex problems in innovation management often need the collaboration of various experts to create novel solutions. Interestingly, although common sense suggests that individuals are more creative in a group context, research indicates that this is oftentimes not the case. The question on how to structure creative processes in groups in such a way that groups can actually benefit from their creative potential is therefore crucial. Paul Paulus has spent much of his academic career addressing this intriguing question. He and his research team have discovered many factors that influence group creativity and have been able to demonstrate conditions under which group interaction enhances creativity. For the past eight years he has been working with a multidisciplinary team to better understand the cognitive, neural and social factors that underlie the group creative process (Paulus et al., ). They are presently funded on a three year project to investigate innovation processes in networks.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.037 | 0.008 |
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".