Bibliographic record
Abstract
Do people talk about death? Many scholars argue that people in our society do not talk about death; that it is taboo, it is denied or sequestered into hospitals and funeral homes and exists outside of everyday life. And yet, others argue that death is “a very badly kept secret” with hundreds of books published on the topic in the last few decades, most of them claiming that we cannot talk about death. This disconnect leads some to argue that there is a revival of death happening instead. My research sits at the nexus of this tension; I attended death cafés around Southern Ontario to explore the dialogues that emerge in spaces set out to break the presumed taboo around death. At a death café people are meant to “drink tea, eat cake, and talk about death.” The objective of these events is “to increase awareness of death with a view to helping people make the most of their finite lives.” This statement, from the official death café website, assumes that facing death will help to make sense of, and give perspective to, life. I explore how and if death cafés accomplish their intended purpose of encouraging existential discussion, and if such a discussion was in fact beneficial to the attendees. I argue that the discussions at the death cafés I attended did not seem to fulfill the purpose stated on the website of encouraging existential discussion about one’s own death. I then situate this observation in the context of broader understandings of the denial of death thesis generally and in terms of residual Victorian romanticism and attachment to others.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.046 | 0.015 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".