The paradoxical relationship between sense of power and creativity: Countervailing pathways and a boundary condition
Bibliographic record
Abstract
Abstract When sense of power helps or hinders creativity remains an unresolved question. Drawing upon the approach‐inhibition theory of power and its extensions, we integrate two different predictions into a dual‐pathway model, showing the paradoxical role that sense of power—one's perceived ability to influence others—plays in predicting creativity. Specifically, sense of power helps creativity through increased risk‐taking and simultaneously hinders it through reduced perspective taking. We further propose openness to experience as a moderator of the countervailing mechanisms, such that the positive path through risk‐taking is stronger and the negative path through perspective taking is weaker for individuals with higher (vs. lower) levels of openness. We test our hypotheses with three multisource and multi‐wave field studies (Study 1: n = 181 part‐time MBAs paired with peers; Study 2: n = 128 sales employees paired with store managers; Study 3: n = 153 sales employees paired with store managers). The results support our theoretical model, showing that sense of power and creativity are simultaneously connected positively through risk‐taking and negatively through perspective taking, and that the overall indirect effect of sense of power on creativity is more positive for individuals with higher (vs. lower) levels of openness to experience.
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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 | 0.003 | 0.021 |
| 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 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".