Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In this article I will discuss the dancer’s physical potential and the sensitive knowledge (‘la connaissance sensible’) that emerges from dance practice. For this, I take Lévi-Strauss’ (2010) theory of the ‘savage mind’ as a reference. This theory is important to understand how the discipline of dance does not need to be justified through modern science (Lévi-Strauss 2010). It is understood that dance operates from sensitive knowledge, while modern science is expressed through the intelligible. I will point out how the dancer operates the sensitive, or dancing, thought, stressing that this type of knowledge is created through interest in how to use it and not through interest in how it serves, or what it means. I will then explain how, through sensitive knowledge, dancers propose new challenges during their aesthetic training in order to develop new body technologies, thereby increasing their expressive potential. For this, dancers need to develop body acuity. In other words, I will discuss the processes that dancers use to transform the perception of the self and of the world through danced gestures. In this process, the dancer is always looking for new challenges; he/she constantly deals with new risks in order to discover new knowledge. I will also discuss the problem that dance faces in traditional academia, which disregards sensitive knowledge and values scientific knowledge.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it