Time, trauma, and the brain: How suicide came to have no significant precipitating event
Bibliographic record
Abstract
In this article, we trace shifting narratives of trauma within psychiatric, neuroscience, and environmental epigenetics research. We argue that two contemporary narratives of trauma - each of which concerns questions of time and psychopathology, of the past invading the present - had to be stabilized in order for environmental epigenetics models of suicide risk to be posited. Through an examination of these narratives, we consider how early trauma came to be understood as playing an etiologically significant role in the development of suicide risk. Suicide, in these models, has come to be seen as a behavior that has no significant precipitating event, but rather an exceptional precipitating neurochemical state, whose origins are identified in experiences of early traumatic events. We suggest that this is a part of a broader move within contemporary neurosciences and biopsychiatry to see life as post: seeing life as specific form of post-traumatic subjectivity.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.042 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".