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Record W4390066838 · doi:10.3138/seminar.59.4.3

Playful Distance: On the Relationship between Fossils and Time in Eduard Mörike’s “Göttliche Reminiscenz”

2023· article· en· W4390066838 on OpenAlexvenueno aff
Martin Dawson

Bibliographic record

VenueSeminar A Journal of Germanic Studies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicGerman Literature and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSublimePoetryScholarshipObject (grammar)LiteratureFantasyAestheticsFace (sociological concept)PoliticsNegationHistoryPsychoanalysisArtPhilosophyPsychologyLinguisticsLaw

Abstract

fetched live from OpenAlex

The nineteenth-century author Eduard Mörike is difficult to pin down. In some previous characterizations, Mörike has appeared as a provincial poet, one whose conversational tone, folksy compositions, and tendency towards fantasy lend him an unserious quality. While modern scholarship has shifted to debating the level of his political involvement and his status as a postclassical or proto-modern author, one characteristic stands out among the majority of descriptions: the playful quality of his works and the characters within them. Dreams, memory, encounters with art, idle pastimes—all common topoi in Mörike’s literary output—represent playful events in which varied spatiotemporal relationships emerge, especially in the face of potentially traumatic encounters with death, sickness, or the sublime. Mörike’s handling of the fossil in “Göttliche Reminiscenz” involves such an encounter. In the nineteenth century, fossils often set the stage for a traumatic encounter with vast expanses of non-human time. Mörike’s playful treatment of the subject offers a productive approach to the sublime that moves beyond a simple negation of its traumatic nature. In Mörike’s poem, the fossil exists as both a sublime thought figure and an intimate lyrical object, offering another way to conceptualize non-human experience.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.095
GPT teacher head0.313
Teacher spread0.218 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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