A methodology of (un/re)making: a kitchen table conversation with an early career scholar-educator-practitioner collective
Bibliographic record
Abstract
Performance is integral to everyday life, especially for early career scholars navigating multiple minoritisations (e.g. racialisation, neurodivergence). From how we dress to how we move through spaces; we continuously negotiate and perform our identities. For such scholars, performance is a site of queer world-making (Muñoz 1999), reorienting relationships to dominant ideologies (Ahmed 2006) and imagining queer futures (Muñoz 2009). Using the kitchen table as a ‘methodology of the making’ (Mattes and Farrell Racette 2019) and grounded in applied performance practices (Mackey and Whybrow 2007), we explore embodied identities in liminal spaces, presenting a manuscript which synthesises our creative work and provocations.
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 | 0.017 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.025 | 0.043 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".