Creativity from paradoxical experience: a theory of how individuals achieve creativity while adopting paradoxical frames
Bibliographic record
Abstract
Purpose Extant paradox theory suggests that adopting paradoxical frames, which are mental templates adopted by individuals in order to embrace contradictions, will result in superior firm performance. Superior performance is achieved through learning and creativity, fostering flexibility and resilience and unleashing human capital. The creativity mechanism of paradox theory is limited by a few propositions and a rough underlying theoretical logic. Using the extant theoretical base as a platform, the paper aims to develop a more powerful theory using a computational simulation. Design/methodology/approach This paper relies on a psychologically realistic computer simulation. Using a simulation to generate ideas from stored information, one can model and manipulate the parameters that have been shown to mediate the relationship between paradoxes and creative output – defined as the number of creative ideas generated. Findings Simulation results suggest that the relationship between paradoxical frames and creative output is non-monotonic – contrary to previous studies. Indeed, findings suggest that paradoxical frames can reduce, rather than enhance, creative output, in at least some cases. Originality/value An important benefit of adopting paradoxical frames is their capacity to increase creative output. This assumption is challenging to test, because one cannot measure private cognitive processes related to knowledge creation. However, they can be simulated. This allows for the extension of current theory. This new theory depicts a more complete relationship between paradoxical frames and creativity by accounting for subjective differences in how paradoxical frames are experienced along two cognitive mechanisms – differentiation and integration.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".