Martyrs’ Last Letters: Are They the Same as Suicide Notes?
Bibliographic record
Abstract
Of the 800,000 suicides worldwide every year, a small number fall under Emile Durkheim's term of altruistic suicides. Study on martyrdom has been limited. There has to date, for example, been no systematic empirical study of martyr letters. We examined 33 letters of Korean self-immolators, compared with 33 suicide notes of a matched sample of more common suicides. An analysis of intrapsychic factors (suicide as unbearable pain, psychopathology) and interpersonal factors (suicide as murderous impulses and need to escape) revealed that, although one can use the same psychological characteristics or dynamics to understand the deaths, the state of mind of martyrs is more extreme, such that the pain is reported to be even more unbearable. Yet, there are differences, such as there was no ambivalence in the altruistic notes. It is concluded that intrapsychic and interpersonal characteristics are central in understanding martyrs, probably equal to community or societal factors. More forensic study is, however, warranted.
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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".