From flow to mystical experiences: Connecting entropy and fluency along the unifying framework of cognitive continuum
Bibliographic record
Abstract
Self-transcendent experiences (STEs) represent profound shifts in cognition and consciousness, possessing significant transformative potential. With growing scientific interest in these phenomena, we propose the cognitive continuum as a unifying framework. Grounded in enactive cognitive science and complex dynamic systems perspectives, this approach takes the embodied person, embedded within their world, as the appropriate unit of analysis. The continuum illustrates how STEs, such as flow states and mystical experiences, reflect an enhancement of relevance realization, the organism’s active engagement with its environment to adaptively frame its world, across increasingly global levels of cognitive organization. We identify destabilization and complexification as central processes in this enhancement and propose entropy as their metric. We introduce the Entropy-Fluency hypothesis, which posits that increased entropy signals destabilization followed by increased fluency, thereby conceptually bridging first-person subjective experiences with third-person scientific observations of STEs. The cognitive continuum reveals STEs as dynamic, person-specific, and context-dependent phenomena emerging from person-world coupling, requiring idiographic and transdisciplinary methodological approaches. This framework provides conceptual tools for understanding these profound experiences, contributing to a comprehensive science of human flourishing.
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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 | 0.002 | 0.007 |
| 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 | 0.015 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".