Bibliographic record
Abstract
This essay investigates the negative consequences of higher education’s ableist obsession with individualism, objectivity, and results, positing practice-based research as a powerful crip alternative to traditional academic models. While traditional models of scholarship aim to separate knowledge from the body that created it, practice-based research locates the body as the source of wisdom, a source to be recognized and celebrated. This essay makes legible the messy bodily experience I had during its writing and intertwines it with an explanation of the autoethnographic research process I undertook to better understand my disabled embodied self during a multi-year creative research process. I situate my experience creating "Awaiting Tiresias" within a tradition of disabled scholar-artist-activists who seek to create time and space for themselves within higher ed. Alison Kafer defines this experience in Feminist, Queer, Crip as reimagining “notions of what can and should happen in time” and “bend[ing] the clock to meet disabled bodies and minds” (27). Indeed, crip scholarship prioritizes the health of those who engage in it and the transformations that occur through the research and dissemination process instead of results. This essay argues that through its commitment to challenging assumptions, participating in ongoing and collaborative research methods, and recognizing the central role of the researcher’s body in the research process, practice-based research serves as a crip intervention in ableist scholarship practices.
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 | 0.118 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.023 | 0.135 |
| Scholarly communication | 0.036 | 0.040 |
| Open science | 0.006 | 0.042 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".