Fascias: Methodological Propositions and Ontologies That Stretch and Slide
Bibliographic record
Abstract
This commentary introduces fascia, our bodily connective tissue, as a contribution to thinking body as process beyond mind–body dualisms. Research in the field of Fascia Studies has shown that fascias’ core qualities are shifting and sliding in tensional responsiveness and that its both/and tissue- and-system features challenge clear-cut definitions. Acknowledging these characteristics of human physiology in novel ways, and in particular fascia as our largest sensory organ, becomes relevant to ontologies, alterities and research methodologies emphasizing experience and transdisciplinarity. Importantly, the notion is never to theorize fascia as model or metaphor but as quotidian processual responsive proposition.
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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 | 0.034 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.009 | 0.076 |
| Scholarly communication | 0.016 | 0.036 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.009 | 0.017 |
| Insufficient payload (model declined to judge) | 0.006 | 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".