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Record W4405438791 · doi:10.1086/731826

“Happy Are the Professors”: Strasbourg, the Spirit of Synthesis, and the Unification of Historical Knowledge

2024· article· en· W4405438791 on OpenAlexaff
Kriston R. Rennie

Bibliographic record

VenueHistory of Humanities · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Architecture and Urbanism
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsUnificationPhilosophyLiteratureEpistemologyHistoryArtComputer scienceProgramming language

Abstract

fetched live from OpenAlex

In the 1920s, the University of Strasbourg became the institutional birthplace of creative interdisciplinary scholarship, innovation, and historical synthesis. The structure, personnel, and academic culture of this northeastern Alsatian institution cast an enduring light on the French historical tradition. Assuming a leading role in the development of a synthetic approach to history, Strasbourg’s relationship with the discipline advanced its central position in the evolution of scientific knowledge and practice. By examining the conditions at Strasbourg that generated the field of history’s intellectual spirit and collaborative activity, this article explores the ripe human and physical environment in which synthetic ideas were born, championed, and imprinted on the academic discipline. The institutional and organizational framework of the new French university, it will be argued, contributed to the successful practice, growth, exchange, and unification of historical knowledge that shaped and inspired the profession more broadly in the first half of the twentieth century.

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)0.012
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.051
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0130.041
Scholarly communication0.0140.010
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.224
Teacher spread0.157 · 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
Published2024
Admission routes1
Has abstractyes

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