Bibliographic record
Abstract
When C. G. Jung partnered with Sigmund Freud, he already had a broad knowledge of world mythology and an understanding of the unconscious formed largely from Schopenhauer’s Will and Nietzsche’s Dionysian energy of nature, or physis. Unwilling to reduce this unconscious—matrix of dreams, myth, and literature—to Freud’s infantile sexual libido, Jung’s break with Freud was inevitable. His long suppressed ideas emerged in Symbols of Transformation, a mythically enriched study of regression in service of development, which rejects Freud’s limited libido. This paper uses Heidegger’s phenomenology to purge remaining traces of psychic encapsulation from Jung’s significant archetypal insights and demonstrates the modified Jungian articulation in the context of Thomas Mann’s novel, Magic Mountain, a study of hermetic individuation. Not only does this paper use Jung’s insights to clarify the labyrinthine development of the novel, thereby taking sides in a literary debate about its meaning, but it uses Mann’s artistic insights to expose limitations of Jungian theory.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.042 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".