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Record W2768850171 · doi:10.1515/iasl-2017-0015

Weltreisen, Weltwissen, Weltvergleich – Perspektiven der Forschung

2017· article· en· W2768850171 on OpenAlexaboutno aff
Walter Erhart

Bibliographic record

VenueInternationales Archiv für Sozialgeschichte der deutschen Literatur · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAlexander von Humboldt Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEthnographyGeorge (robot)HistorySociologyArt historyAnthropology

Abstract

fetched live from OpenAlex

Abstract After giving an overview of the development of and recent trends in research on world travel literature of the 18th and 19th centuries, this article considers new research perspectives by linking world travel literature, the history of science, and the history of literary forms. While the latest research has drawn attention to the importance of studying the multiplicity of travels, contexts, practices, sources, logbooks, and travel reports, this essay identifies ‘comparison and comparing’ as a historical key concept in the making of world travels as a genre and a starting point for the formation of early global perceptions about science, nature, and cultural difference. After drawing on various travel authors like Georg Forster, George Vancouver, Alexander von Humboldt, and Adelbert von Chamisso, the article finally aims at identifying new research directions by reconstructing both groups of historical actors, the ‘natives’ and the sailing Europeans, as distant objects of ethnographic literary studies.

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)0.005
metaresearch head score (Gemma)0.004
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 score0.013
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0060.023
Scholarly communication0.0130.007
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.022
GPT teacher head0.315
Teacher spread0.292 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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