Constructing a World for Compassion: How Temporal Work Can Preserve Compassion in Extreme Contexts
Bibliographic record
Abstract
Abstract This article extends previous research on how compassion can be preserved in extreme contexts, highlighting the phenomenological experience of time in practices. Based on an ethnographic study of hospice care, we show how temporal work preserves compassion by enacting the end‐of‐life as a time of agency, a liminal time between the past (life) and an undesirable and certain future (death) that shifts focus to here and now actions. Taking a Heideggerian approach to the lived experience of compassion, we understand the hospice as a world where different ways of being are implicated in practices organized through existential spatiality (being with the guest and being by the guest). We show how exposure to people in end‐of‐life affects the experience of time in compassion practices, allowing them to be experienced as kairos, involving sacredness and spiritual connectedness with others, and as chronos, allowing compassion‐givers to restore their capacity by focusing on compassion tasks.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.032 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".