CREATIVITY AND INNOVATION: STATE OF THE ART AND FUTURE PERSPECTIVES FOR RESEARCH
Bibliographic record
Abstract
Creativity is a vibrant field of scientific research with important applied implications for the management of innovation. In this article, we argue that the proliferation of creativity research has led to positive and less positive outcomes and discuss five relevant research themes. We first introduce our readers to the different proposed dimensions of a creative object. Next, we explain recent developments on the level of the creativity magnitude issue. Based on that, we review how researchers currently operationalize creativity. After discussing how creativity is conceptualized and operationalized, we outline how it might be enhanced. Finally, we present an overview of the wide variety of methodological approaches currently used in creativity research. We close by calling for more interdisciplinary research and offering other suggestions for future directions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.035 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.022 | 0.036 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.014 | 0.014 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".