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Animals and Emotions in Medieval German Literature: The Various Functions of Bestial Imagery in the Staging of Emotions

2024· article· en· W4392734181 on OpenAlexvenueno aff
Sandra Hofert

Bibliographic record

VenueAestimatio Sources and Studies in the History of Science · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical, Literary, and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGermanHistoryPsychologyLiteratureArtArchaeology

Abstract

fetched live from OpenAlex

This article, which continues ideas developed in the context of the Deutsche Forschungsgemeinschaft: Graduiertenkolleg 1876—215342465 (GRK1876), examines how animals are used in medieval texts to (re)present, shape, and develop the literary representation of emotions. On the basis of selected examples, it shows how diverse the literary functions of animal imagery can be and how many different poetic and aesthetic strategies can be found for staging animals, connecting them with human characters and the recipientsof the tale. In this way, animals can serve as objects of cultural self-reflection and as models for philosophical orientation. bySandra HofertFriedrich-Alexander-University Erlangen-Nurembergsandra.hofert@fau.de

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 score0.004
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0030.017
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0010.001
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 head0.053
GPT teacher head0.286
Teacher spread0.233 · 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
Published2024
Admission routes1
Has abstractyes

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