For a Choreography of Emotions: Spatiotemporal Phenomenology
Bibliographic record
Abstract
BACKGROUND: Emotions are a key feature of human life. Despite intensive research, we still do not have a full grasp of the complexity of emotions, such as their peculiar combination of emotional feeling and behavioral motor manifestation. We also lack translational research that links the phenomenal (experiential) with the pre-phenomenal (neurological) levels. SUMMARY: Operating within the framework of embodiment on experiential and neural levels, we characterize different emotions by their different movements as well as by their distinct experiences of time and space, rather than externally observable behavior. This leads literally to a choreography of emotions and spatiotemporal phenomenology, that is, a characterization of emotions in terms of corporeality, particularly how persons feel that their body moves in space and time and interacts with its environment. That is complemented by an outlook of linking such views of emotions to the brain through what has recently been introduced as "Spatiotemporal Neuroscience," whose theoretical background is briefly sketched and outlined. This is accompanied by an example of the temporal changes, with abnormal slowness being shared by both, experience and brain, as their "common currency" during sadness. KEY MESSAGE: We here introduce the outline of a choreography of emotions as a descriptive framework that makes reference to the direction and timing of the way persons experience their bodily movement, as well as to the matching of bodily movements and the surrounding lived space, which carries high potential of being directly linked to the brain in a non-reductive way through spatiotemporal neuroscience.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".