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Record W2416863373 · doi:10.15173/sj.v3i1.2936

Vienna’s Feuilletons from 42nd Street: Culture and Civilization in Ann Tizia Leitich’s Amerika, du hast es besser (1926)

2016· article· en· W2416863373 on OpenAlexvenueno aff
Rob McFarland

Bibliographic record

VenueThe Sophie Journal · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicGerman Literature and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCivilizationJazzIdeologyCulture of the United StatesPower (physics)Popular cultureBeautyAppropriationSymphonyArt historyNewspaperArtHistorySociologyAestheticsLiteratureMedia studiesPolitical sciencePoliticsLawPhilosophy

Abstract

fetched live from OpenAlex

While so many of her fellow European writers, like Zweig, either naïvely celebrated the mechanical wonders of Henry Ford’s factories or made paranoid forecasts of American jazz music squelching out Europe’s symphonies and concertos, the author of those lines, Ann Tizia Leitich (1891-1976), contended that America is much more than an ideological projection space for Europe’s hopes and fears. As the American correspondent for Vienna’s influential Neue Freie Presse newspaper, Leitich chronicles the complexity and power of the United States from a specific, personal and intimate perspective. In this article, I will argue that Leitich counters the popular interwar perception of Europe as a beautiful, doomed culture that is under attack by a soulless but powerful American civilization. Focusing on her appropriation of Oswald Spengler’s dichotomy between civilization and culture, I will explore Leitich’s concept of a cultural syncretism that combines artistic beauty and economic power in a mutually beneficial relationship.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.012
GPT teacher head0.200
Teacher spread0.188 · 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
Published2016
Admission routes1
Has abstractyes

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