Navigating the Genealogies of Trauma, Guilt, and Affect: An Interview with Ruth Leys
Bibliographic record
Abstract
In this interview, Ruth Leys discusses her career as a historian of science and her research on contemporary developments in the human sciences, including Trauma: A Genealogy, From Guilt to Shame: Auschwitz and After, and her current work on the genealogy of experimental and theoretical approaches to the affects from the 1960s to the present. Among the topics she covers are her investigation of the role of imitation or mimesis in trauma theory; why shame has replaced guilt as a dominant emotional reference in the West; the ways in which the shift from notions of guilt to notions of shame has involved a shift from concern about actions, or what you do, to a concern about identity, or who you are; why the shift from agency to identity has produced as one of its consequences the replacement of the idea of the meaning of a person's intentions and actions by the idea of the primacy of a person's affective experience; the significance of the recent “turn to affect” in cultural theory; and why the new affect theorists are committed to the view that the affect system is fundamentally independent of intention and meaning because they view it is a material system of the body.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.030 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 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".