Bibliographic record
Abstract
Abstract This paper argues that grieving a profound loss is a transformative experience, specifically an unchosen transformative experience, understood as an event‐based transformation not chosen by the agent. Grief transforms the self (i) cognitively, by forcing the agent to alter a large set of beliefs and desires, (ii) phenomenologically, by altering their experience in a diffuse or global manner, (iii) normatively, by requiring the agent to revise their practical identity, and (iv) existentially, by confronting the agent with a structuring condition of their life. Grief is a disruption to one's identity that an agent addresses by making sense of the world after the loss, remaking the practical significance of various situations in their lives through their activity. Transformative grief is both an “activity” and a “revelation” (Callard, 2020): Some parts of the grieving process are active (the agent must actively work to become a new kind of person), while others are irreducibly passive (the agent passively undergoes them).
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.035 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".