From Spectrum to Prism: Shifting Positions on Dance Dramaturgy—a Conference Response
Bibliographic record
Abstract
Three dramaturgs working with dance artists in Canada were tasked to share a summary and response to the Society of Dance History Scholars conference on dance dramaturgy in Toronto (2011) at a plenary closing panel. This article offers Pil Hansen's contribution to the panel alongside comments from DD Kugler and Jacob Zimmer. Perspectives presented at the conference by Bojana Bauer, Bonnie Brooks, Thomas DeFrantz, Christina Goletti, Elizabeth Kattner, Gabriele Klein, Jodie McNeilly, Selma Odom, Katherine Profeta, Freya Vass-Rhee, and Laura Vriend are recalled with a proposal to use them as a prism that can advance the field instead of regarding them as opposing positions and definitions.
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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 | 0.023 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.018 | 0.017 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.012 | 0.018 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".