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Record W2767926976 · doi:10.3138/seminar.53.4.02

Place, Motion, and Guilt in Wilhelm Raabe’s <i>Stopfkuchen</i>

2017· article· en· W2767926976 on OpenAlexvenueno aff
John B. Lyon

Bibliographic record

VenueSeminar A Journal of Germanic Studies · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicGerman Literature and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMotion (physics)GlobeDisplacement (psychology)GermanModernityCollective responsibilitySense of placeConnection (principal bundle)PsychologySociologyPhilosophyPsychoanalysisEpistemologyComputer scienceTheologyMathematicsArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

Wilhelm Raabe’s novel, Stopfkuchen (1890) highlights inescapable guilt, guilt that is both bound to specific places and that can travel great distances. The themes of guilt, place, and motion are interconnected in this novel, and the novel marks a modern shift in the understanding of these themes. It traces an emerging awareness of both the narrator’s individual guilt in a more traditional sense and the collective guilt of his town and of German culture in a more modern sense. This guilt is both connected to place and dissociated from it, suggesting both a pre-modern connection to place and a sense of displacement typical of modernity. By the end of the novel we find a sense of inescapable guilt that both resides in specific places and compels the guilty toward motion. It makes specific places unheimlich even as it extends across the globe.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.015
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.042
GPT teacher head0.296
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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