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Record W4414672242 · doi:10.18254/s207987840035310-0

Illustrating Travelogue: Crimea’s History in French Travel Writing of the First Quarter of the 19th Century

2025· article· en· W4414672242 on OpenAlexaboutno aff
Никита Храпунов

Bibliographic record

VenueIstoriya · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsPeninsulaPossession (linguistics)Quarter (Canadian coin)Travel writingKingdomCultural heritageNarrativeValue (mathematics)

Abstract

fetched live from OpenAlex

This author of the article analyses the uses of the past of the Crimea and the images of archaeological monuments located in the Crimean Peninsula in French travelogues from the late 1800s and 1810s. This region features a unique concentration of cultural heritage sites of various chronological periods and cultures; its rich history traditionally attracted foreigner writers. By the early-nineteenth century, the travellers had in possession fundamental researches on the history of the Crimea and the North Black Sea Area written in French (or translated into French) by Charles de Guignes, Johann Thunmann, Vicenzo Formaleoni, and Stanislas Sestrencewicz de Bohusz. The travellers could also use the heritage of their forerunners: Charles de Peyssonnel, François de Tott, Charles de Ligne, Jean Reuilly, and others. Therefore, the travelogues under present study, created by Charles Pictet de Rochemont, Paul Guibal, Jacques-François Gamba, and “François Mersier” (Just-Jean-Étienne Roy), use history to play an auxiliary role of vignettes or decoration, which do not have particular value in itself, but is capable of animating the story, making the latter lively and romantic, arising the reader’s interest, and underlining specific and exotic image of the Crimea as the country featuring rich cultural heritage and located between East and West. The research has shown that the travelers sometimes used history for their narrow specific purposes: to substantiate economic projects, to aggrandize the works of one’s patron, or to “reveal” Russia’s aggressive plans for world’s politics.

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)0.002
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 score0.272
Threshold uncertainty score0.540

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0100.007
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.015
GPT teacher head0.198
Teacher spread0.182 · 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
Published2025
Admission routes1
Has abstractyes

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