Bibliographic record
Abstract
This article is about two interconnected subjects: the politics of acute illness and the representation of such politics in writing. I present three narratives that were provoked by the witnessing of family member’s hospitalization. The narratives focus on the experience of technology and fall within autoethnographic traditions (Denzin, 2003; Ellis & Bochner, 2000; Richardson, 2000), as well as the burgeoning realm of publications that narrate authors’ experiences of the illness of a loved one (Dideon, 2005; Oates, 2011; Want, 2010). In taking seriously the “emergent nature of critical inquiry” (Denzin, 2010), I intentionally move in and out of the narratives inorder to demonstrate how negotiations with “everyday technology” are taken-for-granted. I concern myself with how technology is the primary mode of care and argue that its prolific use calls for a politicization of medicine such that we can see how patients and medical staff alike are configured as mechanistic.
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 | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".