Comparing premodern melancholy/mania and modern trauma: An argument in favor of historical experiences of trauma.
Bibliographic record
Abstract
Historians and psychiatrists have repeatedly looked to both real and imagined individuals of the past, like Achilles and Samuel Pepys, and found evidence that they were suffering from symptoms of trauma and posttraumatic stress disorder. The assumptions that allow such historical "diagnoses" have, however, recently been called into question by philosophers such as lan Hacking, anthropologists like Allan Young and psychiatrists such as Patrick Bracken. These scholars have all suggested in various ways that experiences of trauma could not have occurred until the diagnosis of trauma and its symptoms had been formalized and the language of trauma had been developed in the late 19th century. This article attempts to resolve this bifurcation of opinion on the universality of the mind and historical experiences of trauma in two ways. First, it argues for the necessity of applying modern categories of analysis to further present understandings of the past. Second, it considers discussions of"melancholia" and "mania" in premodern medical literature and argues that there are enough similarities between the causes and symptoms of these premodern disorders and modern trauma to suggest that experiences of trauma may not be wholly culturally bound to the modern world, as the above scholars have suggested. While melancholy or mania cannot simply be understood as premodern names for trauma, and it is not always correct to "diagnose" a premodern person who exhibits symptoms of these illnesses with trauma, such an assumption is not always ahistorical or incorrect either.
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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 | 0.016 |
| 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 | 0.017 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".