Bibliographic record
Abstract
Abstract: I am being haunted by a dance I saw more than a year ago. Ever since it was performed as part of the Actions of Transfer: Women’s Performance in the Americas conference at UCLA in November 2008, I have been reviewing it in my mind every few weeks. I am unsettled by its seeming simplicity and by the integrity and power that this simplicity conveys. Therefore I am writing not about a work I have just seen, but rather one I have been rewatching for several months. The dance, titled Woman and Water , was created and performed by Alutiiq artist Tanya Lukin Linklater. It premiered on 22 May at Visualeyez 2006, Canada’s seventh annual festival of performance art, produced by Latitude 53 Contemporary Visual Culture; the festival’s theme was “Domesticity,” and it was curated by founder Todd Janes in Edmonton, Alberta. When she was invited to UCLA, Lukin Linklater inquired about the availability of water near the conference where the piece might be performed, and, upon seeing the site, determined to stage the work in the plaza in front of Royce Hall, which is adjacent to a large fountain. This is what I remember watching:
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 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.048 | 0.006 |
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".