J.C. Ameisen, D. Hervieu-Léger, and E. Hirsh (Eds.). Qu'est-ce que mourir?Paris: Le Pommier/Cité des sciences et de l'industrie, 2003.
Bibliographic record
Abstract
ABSTRACT Researchers in the fields of biology, religious studies, history, medical ethics, philosophy, and sociology offer a popularized interpretation of “what is death and dying.” This book is divided into three sections, each beginning with a relevant discussion on the contexts of the issue of death and dying. The work proposes three insights into the subject. First, the image of “the dead and the living,” as presented in art history, is revisited through the genetics and biology discourses that have recently challenged the traditional concepts of aging, as well as the very definition of “clinical” death. Second, the “experience of death” is based on new ideologies that reassess the solitude and individualistic nature of the dying and the necessity of reestablishing the links between the dying and the living, as reiterating the cultural norm. Finally, the “good death” establishes a virtual breach between two types of mythical figures – the heroes and the saints – and the relational singularity of palliative care.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.021 |
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".