A Closer Look at Transitions between the Generative and Evaluative Phases of Creative Thought
Bibliographic record
Abstract
Creative thinking is often viewed as a dynamic process that involves shifts between two distinct modes (or phases) of thought—a generative and an evaluative mode. The generative mode involves the generation of new ideas, whereas the evaluative mode involves cognitive and affective evaluations of these ideas. Although the neurocognitive underpinnings of these two thought modes have received significant attention, the dynamics of transitions between them remain largely unexplored. Here, we focus on these dynamics and review current evidence from psychology and cognitive neuroscience about the relationships and transitions between the two purported modes of thought. We suggest that two types of evaluative processing—automatic-affective and deliberate (i.e., based in cognitive control)—play pivotal roles in supporting transitions between the generative and evaluative modes. Ultimately, we contend that future research into creative thought should focus on clarifying the timescales at which the two modes of thought may unfold, how the transition rate between them may relate to creative outcomes, and the nature of automatic-affective evaluations made toward thoughts.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".