A Greener Way to Go: Climate Adaptation Imperatives for Western Deathcare
Bibliographic record
Abstract
Death is a universal human experience, yet the ecological impact of the care and disposition of dead bodies is rarely considered, due in part to cultural taboos surrounding the physical reality of death and decomposition. If negative environmental consequences are to be limited, deathcare will need to adapt. Utilizing interviews with funeral directors from the United Kingdom, the United States and Canada, this research project traces how modern burial and cremation came to dominate Western deathcare, including what types of cultural narratives they reflect. The ecological consequences of these practices are examined and alternative options, both the novel and the reclaimed, are explored. Interviewees shared perspectives on many topics, including the potential emotional insufficiency of standard funeral services, the risk for greenwashing in emerging alternatives and the likelihood that cremation will continue to rise in popularity. Finally, factors of change and larger implications of moving towards more sustainable deathcare options are considered. Practitioners spoke of their hopes and expectations about what might change in deathcare in the next decade. Factors of change discussed include: the COVID-19 pandemic, shifting demography and the entrance of more women to the deathcare industry. Additionally, this research explores how novel and reclaimed ways of thinking about and caring for the dead may inspire a more ecologically balanced way of living.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".