Roundtable
Bibliographic record
Abstract
This roundtable shares the first-hand experiences of five crip, disabled, Mad, and/or neurodivergent doctoral students navigating academia in so-called Canada during the COVID-19 pandemic. While we discuss and theorize our experiences of ableism, structural oppression, and inaccessibility in the academy, we also highlight the world-building experiences of solidarity that have emerged for us in crip community, and in particular among fellow crip graduate students. We consider the ways that crip students open up potential for new ways of learning and being by challenging dominant norms of academic productivity, and we also consider what is lost when these students are pushed out of academic spaces. By engaging in 'collective refusal' of the conditions that harm disabled and otherwise marginalized students, new possibilities emerge for connection, community, and radical change. The virtual conversation transcribed here took place over Discord, email, and Google Docs in autumn of 2021 and early winter 2022. This piece embraces multi-tonality, that is, a range of different voices and ways of writing, speaking, and communicating. It is a conversational piece that intentionally blends varied approaches to knowledge-sharing: polemic, citationally-grounded, and personal anecdotes drawn from our diverse lived experiences. There are a number of different themes woven throughout the text, including anecdotes and personal history, solidarity, ableism in the academy, pessimism/failure, community/interdependence/intimacy, and utopia/futurity/demands for the future. While not intended to provide policy guidance or step-by-step instructions for changing academic culture, we also begin to sketch out some of our dreams for an alternative future for disabled scholars. We discuss imagined futures and possibilities, and ask, is a truly crip and/or accessible academic institution possible?
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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 teacher head, 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".