Creativity and romantic passion.
Bibliographic record
Abstract
Romantic passion typically declines over time, but a downward trajectory is not inevitable. Across 3 studies (1 of which encompassed 2 substudies), we investigated whether creativity helps bolster romantic passion in established relationships. Studies 1A and 1B revealed that people with highly creative personalities report not only greater overall passion but also an attenuation in the tendency for passion to decline as relationship duration increases. Studies 2 and 3 explored positive illusions about the partner's physical attractiveness as a possible mediator of the effect of creativity on passion. Cross-lagged panel analyses in Study 2 indicated that being creative is linked to a tendency to view the partner as especially attractive, even relative to the partner's own self-assessment. Path analyses in Study 3 provided longitudinal evidence consistent with the hypothesis that positive illusions about the partner's attractiveness (participant's assessments, controlling for objective coding of the partner's attractiveness) mediate the link between creativity and changes in passion over time. Study 3 also provided longitudinal evidence of the buffering effect of creativity on passion trajectories over time, an effect that emerged not only for self-reported passion but also for objectively coded passion during a laboratory-based physical intimacy task 9 months later. A meta-analytic summary across studies revealed a significant overall main effect of creativity on passion, as well as a significant moderation effect of creativity on risks of passion decline (e.g., relationship length). (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".