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Record W4393134746 · doi:10.1163/9789004468313_026

Transcultural Careers in the Periodical Press: Fleury Mesplet and Paul-Marc Sauvalle as Transatlantic Mediators

2022· book-chapter· en· W4393134746 on OpenAlexfundaboutno aff
Hans-Jürgen Lűsebrink

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEuropean Cultural and National Identity
Canadian institutionsnot available
FundersVlaamse regeringUniversité Laval
KeywordsHistoryArt

Abstract

fetched live from OpenAlex

This contribution addresses transatlantic mediators in the Francophone Canadian press in a twofold way: firstly, in questioning the core concepts of cultural transfer, transcultural mediator, transcultural career, and transcultural biography; and secondly, in presenting case studies on two French Canadian journalists who both were born in France and migrated to Canada after a several-year-long stint in the United States. In fact Fleury Mesplet, a native of Lyon, who worked as a printer and journalist in Philadelphia before emigrating to Canada in order to spread the ideas of the American Revolution and the ideals of Republicanism, and Paul-Marc Sauvalle, born in Le Havre, who, after a three-year interlude as a journalist in New Orleans and Mexico City, became one of the very first French Canadian liberal newsman, were both very influential and even groundbreaking mediators. They seem to illustrate in a paradigmatic way the dynamics of intercultural experiences and the transcultural biographies generating new forms of journalism.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.139
Threshold uncertainty score0.276

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0140.009
Scholarly communication0.0150.006
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0150.002

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 head0.030
GPT teacher head0.269
Teacher spread0.240 · 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 designQualitative
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 routes2
Has abstractyes

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Same topicEuropean Cultural and National IdentityFrench-language works237,207