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Zur Beziehung zwischen Literatur und Recht in der deutschsprachigen Gegenwartsliteratur

2014· article· de· W1993436648 on OpenAlexaff
Sonja Arnold

Bibliographic record

VenuePandaemonium Germanicum · 2014
Typearticle
Languagede
FieldArts and Humanities
TopicGerman Literature and Culture Studies
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

Dieser Beitrag untersucht die Beziehung zwischen den Diskursen Literatur und Recht in der deutschsprachigen Gegenwartsliteratur. Ausgehend von der langen Tradition der sogenannten Dichterjuristen (Goethe, Kleist, Kafka) werden aktuelle Tendenzen dieser Beziehung in den Blick genommen. Nach theoretischen Überlegungen zum Teilaspekt law in literature (Recht in der Literatur) erfolgt die Bestimmung von spezifischen Themen, Genres und ästhetischen Besonderheiten der in Frage stehenden Texte. Als Textgrundlage dienen Romane von Juli Zeh und Ferdinand von Schirach. In dieser Analyse werden auch die Adaptionen für Kino und TV einbezogen (die SerieVerbrechen für den TV-Sender ZDF, die auf Ferdinand von Schirachs gleichnamiger Kurzgeschichtensammlung beruht, und die MiniserieA Menina sem Qualidades, eine Adaption von Juli Zehs Spieltrieb für MTV Brasilien).

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)0.006
metaresearch head score (Gemma)0.022
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: none
Teacher disagreement score0.023
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0120.019
Science and technology studies0.0040.010
Scholarly communication0.0100.010
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0200.001

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.

Opus teacher head0.013
GPT teacher head0.245
Teacher spread0.232 · 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".

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Citations1
Published2014
Admission routes1
Has abstractyes

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