Bibliographic record
Abstract
Points de vue is an interdisciplinary performance integrating solo dance improvisation with contextual and processual information about the activity which is unfolding. The center of this research-creation project is a question: What happens when I improvise? Investigating the question reveals a deep synergy between multiple and complementary modes of inquiry: theoretical reflections, stimulating the development of methodologies, enacted through practices over extended periods of time. These are co-dependent processes, mutually enriching each other through recursive and iterative cycles of inquiry. Improvisation is contextualized through phenomenological accounts, contemporary ideas from the embodied cognition paradigm, and an examination of somatic techniques. The practice is then articulated in the performance through a multiplicity of appearances: experienced through sight, sound, kinaesthetic empathy, words and concepts. Far from contradictory, these multiple points of view contribute to a kind of experiential synesthesia, leading to a richer appreciation of the phenomenon as a whole.
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 | 0.015 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.026 | 0.012 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.075 | 0.023 |
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".