<i>Being in Relationship</i>: Reflections on Dis-Performing, Hospitality, and Accessibility
Bibliographic record
Abstract
This article is from online and personal conversations between members of the Dis-Performing: Disability and Performance Working Group following the graduate student initiative Convergence: Unsettling the Americas: Radical Hospitalities and Intimate Geographies, in Toronto, Ontario, the territory of the Huron-Wendat, the Seneca, and the Mississaugas of the Credit River. As members, allies, artists, researchers, and advocates of Deaf and disability communities, we all experience hospitality and accessibility in many different ways—whether hosting or guesting. This article explores our stories and perspectives on this during and since the Convergence event on 5–7 October 2017. As artists and individuals passionate about creating accessible for all, we discovered the importance of being in relationship with one another to create meaningful conditions of accessibility, beyond concepts of accommodation that put the labour on those needing to advocate for themselves. This article shares the complexities of these relationships through considerations of hosting failures, ethics of creating protocols, interanimation, micro-protections, care, slowness, and the process of invitation. We share strategies we took as a group, and as individuals, to find meaningful spaces and time to host and guest ourselves, both within and outside our working group For us, disability generates different ways of understanding the world, experiencing hospitality, and how to (be) both guest and host.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.020 | 0.040 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".