Bibliographic record
Abstract
In this paper, Jill Carter (Anishinaabe-Ashkenazi) and Jessica Watkin (Blind) reflect on dramaturgical questions about care and safety in performance work they have witnessed or facilitated as scholars, educators, and dramaturgs. Their exchange begins by discussing Erica Violet Lee’s wasteland theory. Acts of reclaiming wastelands emerge as a meaningful framework to reflect on their experience with Indigenous and Disabled people’s approaches to pedagogy, art making, and relationship building. Carter and Watkin turn to Carly Neis’s In My Own Little Corner or Alex Bulmer’s Perceptual Archaeology: Or How to Travel Blind for more concrete examples of Disability performance practice and dramaturgy. The authors draw on these artists’ engagement with language, safety, revelations, reciprocity, and vulnerability to deepen their own reflection on how to build safer spaces with care. Plain Language Abstract (adapted by Kelsie Acton with Daniel Foulds) In this paper, Jill Carter and Jessica Watkin talk to each other. Jill is Anishaabe-Ashkenazi and Jessica is Blind. They think about care and safety together in two performances. The performances are In My Own Little Corner by Carly Neis and Perceptual Archeology: Or How to Travel Blind by Alex Bulmer. They think about: Erica Violet Lee’s wasteland theory. A wasteland is a space, person, or people that a group of people decided should be destroyed and then forgotten. Erica Violet Lee wants us to remember and care for the people and places that are destroyed. She wants to feel sad and find hope for the people and places that are destroyed. In the theatre, thinking about the wastelands means that everyone deserves stories made for them. Everyone deserves stories told by people like them. How stories and language are powerful. Ceremony is a way people are changed. Stories and theatre can work like ceremony to change people. To change, people need to feel safe to share themselves with others. They need to do the hard work of understanding each other. Disabled artists imagine theatre the way it should be, not the way it is. Disability arts spaces need time, thought, and money to reimagine theatre. Everyone needs to be willing to learn and to act on what they learn. Everyone needs the courage to be with, listen to, and respect one another.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.382 | 0.121 |
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".