What would it take to die well? A systematic review of systematic reviews on the conditions for a good death
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The medicalisation of life under the influence of health-care systems, focused on curing diseases, has made dying well challenging. This systematic review identifies common themes from published systematic reviews about the conditions for a good death as a means to guide decisions around this universal event. MEDLINE, Embase, APA PsycInfo, and AMED were searched for citations with "good death" or "dying well" in their titles on Sept 23, 2020, and complemented with backward reference and forward citation screening with Google Scholar. Articles published in peer-reviewed journals in any language were included. Articles that focused on the identification of conditions for a good death and described how primary studies were sought and selected were also included. Data on general characteristics, quality, and themes were extracted independently. 13 of 275 potentially eligible reviews were included. Common themes were dying at the preferred place, relief from pain and psychological distress, emotional support from loved ones, autonomous treatment decision making, avoidance of futile life-prolonging interventions and of being a burden to others, right to assisted suicide or euthanasia, effective communication with professionals, and performance of rituals. No reviews specified the meaning or timing of death, connected themes, or prioritised them. Vague jargon was often used to describe complex concepts. Most conditions for a good death could be offered to most dying people, without costly medical infrastructure or specialised knowledge. Efforts to describe these conditions clearly, to identify whether there are exceptions or missing items, and whether they apply in non-dominant settings (ie, outstide institutional, affluent, anglophone, and Christian settings) are needed.
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.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it