"Aus dem Gesicht verloren": Lavater's Physiognomical Shade and the Coming-Out Story of Chamisso's Peter Schlemihl
Bibliographic record
Abstract
Adelbert von Chamisso's novel Peter Schlemihls wundersame Geschichte (1814) is commonly understood as a criticism of the paradigms of social acceptance, of the way one part of society excludes those it sees as different. It traces Schlemihl's attempts to achieve recognition in several spheres of life. At various moments, he mingles with the moneyed classes or appears to be an aristocrat or an intellectual, as well as being a traveller, a man on the street, an employer, or a groom, and, finally, he is someone who bargains with other men. But when Schlemihl loses possession, first, of his letter of reference and, then, of his shadow, the story shows just how difficult acceptance can be without the components that give shape to a person's identity. The shadow and letter of reference are evocative of the visual and written representations used in physiognomical discourse in the early Goethezeit. Especially Johann Caspar Lavater's Physiognomische Fragmente (1775-78) theorized the use of images and descriptions of the face as a purportedly scientific way to acquire knowledge of an individual's, a gender's, or an ethnic group's predetermined moral, social, or cultural significance. This article discusses the link between physiognomy and the fate of Chamisso's protagonist. The attention given to Schlemihl's shadow and reference letter suggests that Chamisso's work is a document of the conventions and reception of Lavater's physiognomic treatises. The loss of shadow and letter deprives physiognomic practice of its empirical representations and, consequently, signals that Chamisso's novel sees a problem with physiognomy. Physical descriptions in Peter Schlemihl are few in number, scant in detail, and rather generic. Yet Chamisso's novel is fundamentally concerned with the implications of a physiognomical world. One of Chamisso's working titles for the novel included the subtitle Als Beitrag zur Lehre des Schlagschattens (Boyd xxiii [n]) and the 1838 French edition added to the preface a tongue-in-cheek account of the physical meaning of the shadow referring to a section of Rene Just Hauy's Traite elementaire de physique. The story is motivated entirely by the protagonist's
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.039 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".