Bibliographic record
Abstract
This article is about the major contribution of Marcel Proust to psychoanalysis in his seven-part novel, A La Rècherche Du Temps Perdu (translated as Rembrance of Things Past, 1934). This work spans two decades, from 1988, when Proust writing to 1927, when the last part was published 5 years after his death. Proust, a literary scholar whose knowledge dated to the early Greeks, knew nothing of Freud or psychoanalysis. His major contributions were to the emergence of memory, specifically the exquisite details of the descriptive unconscious, which we can now explain in cognitive neuroscientific terms. Freud wanted to do this for all mental processes in 'The Project'. Proust contributed to the projective aspects of passionate love. Kernberg has pointed out that although psychoanalysts knew about transference love, idealization, and sex, love has only been a subject for us in the 1900s. Proust also wrote of jealousy as a necessary concomitant of love. He proposed that all humans had pluripotential sexuality and recognized the psychodynamics of the perversions in a way that is closer to modern psychoanalysts like Chassuguet-Smirgel. Proust was himself psychologically disabled, with an illness his father called neurasthenia, adding somatic components and abulia, inability to make decisions. We would probably recognize him today as having a borderline personality disorder, with superior cognition, depression, somatization, obsessions, compulsions, phobias, and severe anxiety, which he understood was the result of his inability to separate from his mother. Proust's findings in all these areas are compared with the psychoanalytic literature--Freud, to the present.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.035 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".