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Record W2025074912 · doi:10.1215/0961754x-1456845

Introduction: Warburg's Library and Its Legacy

2012· article· en· W2025074912 on OpenAlexaff
Anthony Grafton, Jeffrey F. Hamburger, Peter Mack, Michael Baxandall, Elizabeth Sears, Georges Didi‐Huberman, Carlo Ginzburg, Joseph Leo Koerner, Christopher S. Wood, Jill Kraye, Michael P. Steinberg, Caroline van Eck, Christy Anderson, Thomas DaCosta Kaufmann, Paul Crossley, Barbara Maria Stafford

Bibliographic record

VenueCommon Knowledge · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMultidisciplinary Warburg-centric Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIrrational numberClassicsNazismWarburg effectThe RenaissanceArt historyHistoryLawArtPolitical science

Abstract

fetched live from OpenAlex

In this introduction to a Common Knowledge special issue on the Warburg Institute, the authors argue that the Institute remains today — as it has been, in different forms, for almost a century — one of Europe's central institutions for the study of cultural history. At once a rich and uniquely organized library, a center for doctoral and postdoctoral research, and a teaching faculty, the Institute was first envisioned by Aby Warburg, a pioneering historian of art and culture from a wealthy Jewish family in Hamburg. Warburg rejected the traditional view that the classical tradition was a simple, purely rational Greek creation, inherited by modern Europe. He argued that it was as much Mesopotamian as Greek in origin, as at home in the Islamic as in the European world, and as often irrational as rational in its content — and on the basis of this rich vision he devised brilliant new interpretations of medieval and Renaissance symbols and ideas. Warburg's chosen associate Fritz Saxl put his creation on a firm institutional base, first in Hamburg and then, after a narrow escape from the Nazi regime, in London. For all the changes the Institute has undergone over the decades since then, it continues to ask the questions that Warburg was the first to raise and to build on the methods that he created.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0060.004
Scholarly communication0.0130.008
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0240.009

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 head0.039
GPT teacher head0.334
Teacher spread0.295 · 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
GenreEditorial

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
Published2012
Admission routes1
Has abstractyes

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