Affects, Trauma, and Mechanisms of Symptom Formation: A Tribute to John C. Nemiah, MD (1918–2009)
Bibliographic record
Abstract
John Nemiah was interested in the impact of emotionally traumatic events on mental and bodily processes and in conceptualizing the psychological defenses and deficits that contribute to the development of psychological and somatic symptoms. He viewed dissociation as the central psychological mechanism in the formation of a spectrum of symptoms, and conceptualized alexithymia as a deficit in the cognitive processing of emotion such that stress-induced arousal could bypass the psyche and produce somatic symptoms. This article briefly reviews some of Nemiah's conceptual ideas and relates them to several new theories and concepts and findings from empirical research. His concept of the 'psychic elaboration' of emotion is consistent with contemporary theories of the cognitive processing of emotions that emphasize the importance of imagery and linguistic symbolizations. Alexithymia is inversely related to mentalization and is associated with insecure attachment styles and emotional trauma, which influence the capacity to regulate affects induced by stressful events. A multiple code theory of emotional information processing links psychological and somatic symptoms to various degrees of dissociation within and between the elements comprising emotion schemas and to compensatory attempts at repair. Recent studies support Nemiah's view that alexithymia and intrapsychic conflicts may both contribute to the pathogenesis of panic attacks. There is also substantial evidence of an association between childhood trauma and the development of somatic disease in adult life. Secure attachments and well-developed capacities for symbolization and affect regulation seem to render individuals more resilient to the traumas and stressful events of everyday life.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 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".