Bibliographic record
Abstract
Early twentieth-century psychoanalytic encounters were typically mediated through the case study, a kind of "sur-narrative"—one constructed from above and temporally beyond the physician-patient encounter — in which the physician fills in what Freud calls "gaps" and "imperfections" of the patient's own repression-addled narrative. However, there are cases in twentieth-century modernism of patients creating their own sur-narratives, not case studies, but homages, which do not so much fill in the gaps as cover them over with layers of idealized memories of the physician-analyst, layers replete with their own imperfections and gaps. This essay examines Siegfried Sassoon's sur-narratives of his encounter with W.H.R. Rivers, autobiographical poetry and fiction that work to transform Rivers from mere physician into a guiding spiritual presence. But fissures of pain disrupt his sur-narratives and reveal the poet-patient unable to escape his past or accept the spiritual future into which he projects his physician, safely beyond the harsh material conditions of the war-torn modern world.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".