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Record W7044321432

Wie lernten Triestiner einmal Deutsch? – Grammatiken der deutschen Sprache für Italiener in der Biblioteca Civica von Trieste (vom 18. Jahrhundert bis zum ersten Viertel des 20. Jahrhunderts)

2022· article· en· W7044321432 on OpenAlexaboutno aff

Bibliographic record

VenueArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/) · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Linguistics and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGermanGrammarQuarter (Canadian coin)VocabularyValue (mathematics)Subject (documents)
DOInot available

Abstract

fetched live from OpenAlex

The article focuses on some grammar books published between the 18th century and the first quarter of the 20th century that are available in the Trieste City Library. Trieste belonged to the Habsburg Empire until 1918 and played an important role as its most important port. As a result, knowledge of German also represented an added value for the population. Our interest is in the way German was learned in Trieste at that time by looking at the most widely used grammars. Until the beginning of the 20th century, grammar books had three main features: 1. the predominant presence of Italian as an indispensable aid to learning German, 2. translation exercises, especially from Italian into German, so that the use of certain frequent phrases could turn into translation routines, and 3. lists of vocabulary for learners to memorise. At the turn of the 20th century, the content of readings and exercises changed. There was a transition from topics of a general nature, including literary ones, to topics that attempted to impart cultural knowledge in the broadest sense, which also reflected the change in the socio-political climate.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.612
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0050.003
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.067
GPT teacher head0.246
Teacher spread0.179 · 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; both teacher heads agree on what is shown here.

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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/)Same topicHistorical Linguistics and Language StudiesFrench-language works237,207