Conceptualizations of “good death” and their relationship to technology: A scoping review and discourse analysis
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
Background and Aims: By the 1960s, medicine experienced technological revolutions that enabled it to control and medicalize death in many circumstances. The modern conceptualization of "good death" emerged in the late 1960s with the beginning of the hospice movement, and palliative care became an official medical specialty in 1987. This project aims to elucidate how the idea of "good death" has been discussed and perceived since then, as well as the impact of medical technologies on death. Methods: The terms "good death," "technology," and "palliative care" were searched. One hundred ninety English sources that discussed "good death" explicitly or implicitly, published between 1987 and 2020, were included in the final analysis. Texts were analyzed for discursive themes related to "good death" and technology and demographic data related to authors, geographies, types of text, and date of publication. Results: The discourse of a "good death" with the patient being in control dominated the archive. Other discourses include a good death being peaceful and comfortable, one where the patient is not alone, and one that is not prolonged. Medical technology discourses are largely negative in the setting of death. Conclusion: Findings indicate a strong critique of the medicalization of death in the literature. This also complements the dominance of discourses on patient autonomy. Medical discourses of "good death" and technology permeate discussion outside of the healthcare context, and there is an absence of spirituality and neutrality in "good death" discourses. The results of this study are relevant for ethics and communication in geriatric and palliative care.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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