Bibliographic record
Abstract
If one practical way to define trauma is to consider it as a chronic inability to access and process catastrophic events, that is, as a systematic and haunting blockage of memory formation and reclamation of past experiences, then historians have an inherent stake in the concept. This basic observation is not new, of course, but until now only historians of the Holocaust have evinced serious and consistent interest in the vast literature on Trauma Studies. Most historians—for example those who work with the distant past, with non-Western societies, or with less extreme historical events—have not had to engage with the historical implications of trauma. In as much as historians use the term, they do so from the lay standpoint that considers trauma as a horrible and tragic man-made event or a natural disaster. In its popular and very elastic usage the event (trauma) and its consequences (always “traumatic”) run the risk of remaining unexplored and largely unexplained, and thus, paradoxically, actually traumatic in the sense of not allowing access to the past. While remaining cognizant of the bland usage of the concept of trauma, the goal of this special issue is to offer a modest commentary on what Trauma Studies can offer to “Other Historians” and, perhaps, on what they can offer in return. The work presented here is of a provisional nature and is the product of a year-long seminar by a diverse group of historians at the Institute of Historical Studies at the University of Texas at Austin and the international conference, “Trauma and History,” that they organized.
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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.032 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".