Creative expertise is associated with transcending the here and now.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Human imagination is bounded. As situations become more distant in time, place, perspective, and likelihood, they also become more difficult to simulate. What underlies the ability to successfully engage in distal simulations? Here we examine the psychological and neural mechanisms underlying distal simulation by studying individuals known for transcending these limits: creative experts. First, 2 behavioral studies establish that creative experts indeed succeed at engaging in vivid distal simulations, compared to less creative individuals. Performance on a traditional measure of creativity (Study 1) and real-world success in creative pursuits (Study 2) corresponded with more vivid distal simulations across temporal, spatial, social, and hypothetical domains. Study 3 used neuroimaging to identify the neural mechanism supporting creative experts' simulation success. Whereas creative experts and controls recruit the same neural mechanism (the medial prefrontal cortex) while simulating common or proximal events, creative experts preferentially engage a distinct neural mechanism (the dorsomedial subsystem of the default network) while simulating distal events. Moreover, creative experts showed greater functional connectivity within this network at rest, suggesting they may be prepared to engage this mechanism, by default. Studying creative expertise provides new insight into the ability to mentally transcend the here and now. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it