Dancing With Land: An Asynchronous Artist Panel
Bibliographic record
Abstract
In this forum, I bring a set of five questions about dancing with land to five contemporary dance practitioners based in and around the city colonially known as Vancouver, constructed on the unceded and ancestral territories of the xʷməθkʷəjˀəm (Musqueam), Sḵwx̱wú7mesh (Squamish), and səl̓ilwətaɁɬ (Tsleil Waututh) First Nations. The artists featured include Michelle Olson of Raven Spirit Dance, Julie Lebel of Foolish Operations, Olivia C. Davies of O.Dela Arts, the OURO Collective, and Lee Su-Feh of battery opera. The questions build on my ongoing research (both academic and artistic) into the politics and kinaesthetics of site- or land-based movement. I seek to spotlight the grounded, refined, and body-based knowledge that dancers and choreographers cultivate in the articulation of their practice.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.047 | 0.007 |
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".