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Record W2969522603 · doi:10.1163/22141332-00603004

Ex-Jesuit Librarian-Scholars Adam František Kollár and György Pray: Baroque Tradition, National Identity, and the Enlightenment among Jesuits in the Eastern Habsburg Lands

2019· article· en· W2969522603 on OpenAlexaff
Paul Shore

Bibliographic record

VenueJournal of Jesuit Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsHistoriographyBaroqueEnlightenmentChurch historyClassicsHistoryArtTheologyArt historyPhilosophyArchaeology

Abstract

fetched live from OpenAlex

The former Jesuits Adam František Kollár and György Pray each devoted much of their careers to work in libraries; thereby contributing to the literary and scholarly culture of the eastern Habsburg lands during the second half of the eighteenth century. Kollár, who left the Jesuits early in his career, authored works defending the rights of the Hungarian crown, and chronicled the history of the Rusyn people, ultimately achieved an international reputation as a scholar, coining the term ethnologia. Pray is remembered for his discovery of the oldest written example of the Hungarian language, his extensive historical publications, and for his role, following the papal suppression of 1773, as “Historiographus Hungariae” (Hungary’s hagiographer). The impact of these scholarly efforts by these former Jesuits was a rich and enduring foundation upon which later Hungarian historiography and library science would be based.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.009
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0010.001
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 head0.034
GPT teacher head0.314
Teacher spread0.279 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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