Bibliographic record
Abstract
The authors revisit how Deaf and choreographic languages were resonantly related in Carbon Movement, a Deaf dance-theatre work with vibrotactile interaction from 2023. Here, we return to the work through two alternating perspectives: (1) the spectator experience of a hearing, disabled dramaturg and (2) the collaborative creation process of the Deaf performer, Connor, and the hearing choreographer, Ainsley. The finished choreography offers a score of human-carbon relationship. The performer enters an unknown space, explores and shapes it with desire, is destabilized by environmental responses, and learns to listen with sensory and relational care. Similarly, Conner and Ainsley entered their collaboration with openness about what they each did not know about choreography, Deaf communication, vibrotactile technology/perception, and accessibility. Helping one another learn American Sign Language or choreographic language through creative exploration, they discovered movement-based and Deaf-centric ways of communicating, collaborating, and knowing together. These process dramaturgical discoveries were transferred to the compositional dramaturgy of the stage work, affecting the performer, the environment, and the spectators through an interactive, vibrotactile score that invites multisensory and relational perception. Plain Language Abstract (adapted by Kelsie Acton with Daniel Foulds) This essay is about making a Deaf performance called Carbon Movements. The people writing are Pil, Connor, and Ainsley. Connor is a Deaf performer. Ainsley is a hearing choreographer. Pil is a hearing, disabled dramaturg. A dramaturg is someone who helps artists make art that has meaning and makes people feel. People might see, hear, smell or feel performance. So, dramaturgy is about making meaning and feeling through the senses. We talk about how signing, drawing, and feeling vibrations are Deaf languages. Signing and drawing helped us create movement. In the dance, Connor builds a relationship with the space. The space has a floor that shakes. When the dance starts, Conor doesn’t know the space. He explores it. There is black sand on the floor. He makes shapes in the sand. The floor shakes. The shapes disappear. Connor learns to listen to the space. When they were making the dance, Connor and Ainsley also needed to listen to each other. Connor didn’t know about dance and machines that shake. Ainsley needed to learn about Deaf communication and access. Together they helped each other learn. They discovered ways of communicating, working, and making knowledge together. They made the dance in a way that values Deaf people and their lives. They shared what they learned through the dance.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.183 | 0.043 |
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".