Bibliographic record
Abstract
When someone is very ill in Canada, the individual is taken under charge of the medical system and put on one of two distinct paths for handling the situation: either acute or palliative care. In the acute path, all available medical technology is deployed to save lives and avoid death, while the main objective of the palliative path is comfort, as death becomes inevitable and expected. The two paths are ordinarily seen as part of a linear process, wherein acute care is initially deployed and palliative care only after acute care is determined ineffective. In practice, however, the two paths are intermittent, as the reasoning repertoires that guide care practices along both paths are constantly renegotiated by care teams. This article follows the decision-making process regarding the use of the ventilator for two individuals at the end of their lives as their care teams alternate between legal, curing, and care repertoires. The entanglement of these repertoires leads to unexpected care practices as patients are shifted from one path to another. In both cases, the transition from acute to palliative care was nonlinear, and the purposes of the possible medical actions that could be taken along the two paths kept changing as events unfolded.
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 | 0.032 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.036 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".