Introduction to Death, Immortality, and Unconscious Fantasy: A Symposium
Bibliographic record
Abstract
Arlene and Arnold Richards’ papers examine a very important and timely topic in psychoanalysis—death, immortality, and unconscious fantasy. Given the aging of our profession and society, this topic is highly relevant clinically and personally. Dr. Arlene Kramer Richards provides a comprehensive, concise, historical overview of the usefulness of the idea of the death instinct, comparing the death instinct, death drive, and unconscious fantasy of what happens after death. Her article focuses on the clinical utility of the construct, while also providing a poignant examination of the major theoretical and philosophical ideas about death by such psychoanalytic titans as Freud, Klein, Spielrein, Arlow, Brenner, and Kohut, among others. Dr. Arnold Richard examines conscious and unconscious fantasies of death and immortality, focusing on the wish for immortality, as expressed in our dreams. He provides a collection of his own dreams, and self-analysis, which demonstrate how the wish for immortality operates in dreams and waking life. He provides highly useful commentary on Freud’s conflicts about his own mortality and its impact on the psychoanalytic theory of human motivation. In addition, he offers an innovative framework for potentially integrating wish-fulfillment dreams and traumatic dreams, and suggests that the wish for immortality might be added to the inventory of primary dream wishes, along with sexual and aggressive wishes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".