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Record W2566797845

К истории традиции «Красного креста» памятников: Шарль Норман, Фердинанд Веттер, Николай Рерих

2015· article· ru· W2566797845 on OpenAlexaboutno aff
Спиридонова Юлия Валентиновна

Bibliographic record

VenueТруды Санкт-Петербургского государственного университета культуры и искусств · 2015
Typearticle
Languageru
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsnot available
Fundersnot available
KeywordsTreatyConventionLeagueLawPolitical scienceQuarter (Canadian coin)Economic historyHistoryArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The tradition of the «Red cross» of monuments united bright cultural figures of France, Switzerland, Russia. Charles Normand (1889) for the first time proposed the conclusion of the international treaty on preservation of monuments during a war. The proposals formulated by Ferdinand Vetter in the project «Golden Cross monuments» (1915) became the result of the destruction of monuments of architecture during the First World War and the ineffectiveness of the Hague Conventions (1899, 1907). The idea «The Red cross of culture» of Nikolas Roerich was embodied in the conclusion written by the countries of the Pan-American Union of the first international treaty on the Protection of Artistic and Scientific Institutions and Historical Monuments (Roerich Pact, 1935). In 1938 after analyzing all these ideas the League of Nations elaborated a draft of the international convention on the protection of historical monuments and works of art during the military operations, which became the basis of the Hague Convention on the Protection of Cultural values in case of armed conflict adopted by UNESCO in 1954. The origins of this idea appeared in the last quarter of the XIX 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)0.001
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: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.007
Scholarly communication0.0060.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.137
GPT teacher head0.294
Teacher spread0.156 · 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
Published2015
Admission routes1
Has abstractyes

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Same venueТруды Санкт-Петербургского государственного университета культуры и искусствSame topicArchaeological Research and ProtectionFrench-language works237,207