Bibliographic record
Abstract
Mirror neurons are specialized neurons which echo the movements perceived in another's body in incipient movements in one's own body, in a kind of involuntary kinesthetic empathy. Their discovery has given rise to a far-reaching reassessment in cognitive science, the arts, and the humanities of the role of empathy and the self-other relation in the constitution of the sense of self. Mirror-touch synesthesia (when a perceived touch to another's body elicits in the perceiver the sensation of being similarly touched) is one of the forms this "empathy" takes. This article takes mirror-touch synesthesia as a jumping-off point to reconsider synesthesia as a whole, and in particular its relation to empathy, and the relation of empathy to movement. It is argued that the usual vocabulary used to analyze these issues -- identi cation, body image, defect or "confusion" in the body's spatial schema -- are vitiated by a cognitivist bias which carries presuppositions that obscure the complexity of the emergent organization of experience. A philosophical rethinking is necessary as a corrective. The article undertakes this project with the aid of process-oriented philosophers C.S. Peirce, Henri Bergson, and A.N. Whitehead, proposing a framework centering on the notion of a "virtual body" composed of the integral mutual inclusion of potential qualities of experience which are selectively "composed" in movement. The emphasis on the performative self-composition of experience involves replacing the prevailing model of cognition with a fundamentally aesthetic model.
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.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.021 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".