Bibliographic record
Abstract
Whether the "call" to write a eulogy comes when we learn of our loved one's death or shortly after, it comes when we may not yet be able to mourn--let alone make a declaration. The death of a loved one may alienate us from the world and from the sense of self that rests on our daily living in the world and with others. It may "individualize us down to ourselves" by throwing us into a world utterly devoid of meaning and anchors. Paradoxically, from this "nothing," a call may usher forth demanding us to take a stand on our loved one's death and ultimately on our being here. Trying to avoid hearing this call when threatened by the nothingness and world-collapse that a loved one's death brings may be the most natural response. But what happens when we are asked to write a eulogy? Can we ignore the call or is it itself inextricably intertwined with our mourning and precisely that which begs to be expressed? This paper describes the experience of eulogizing a loved one as an encounter with the mortality of words, as listening to silence, and as addressing the deceased--without bathos or pathos.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".