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Record W4385424815 · doi:10.5559/di.32.2.04

The Struggle for Commemorating the World War I Centenary as an Illustrative Example of the Attitudes Towards That War in Croatia

2023· article· en· W4385424815 on OpenAlexaboutno aff
Vijoleta Herman Kaurić

Bibliographic record

VenueDrustvena istrazivanja · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
FundersHrvatska Zaklada za Znanost
KeywordsMonarchyWorld War IISpanish Civil WarEconomic historyState (computer science)HistoryFirst world warPolitical scienceNarrativeAncient historyLawClassicsArtPoliticsLiterature

Abstract

fetched live from OpenAlex

The commemoration of the World War I Centenary (2014–2018) was the most important social event in the last decade in the developed countries of Western Europe, especially Britain and France, and in the former British dominions, Canada and Australia. In contrast to these victorious countries, the countries defeated in the war (primarily Germany and Austria) had a significantly more modest and different approach to the commemoration. The emphasis was on all war victims, soldiers and civilians, regardless of which side of the war they had fought on. Since Croatia, as a former part of Austria-Hungary, found itself in a completely new state union after it was united with the Kingdom of Serbia after the war, veterans were ill-advised to mention their participation in the war on the wrong side. It was no better after the end of World War II, when one victor's narrative replaced another, and made the mentioning of formerly existing monarchies completely unacceptable. All these facts influenced attitudes towards World War I, which was almost completely forgotten in Croatia over time.

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)0.003
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: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0210.014
Scholarly communication0.0100.002
Open science0.0010.005
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0020.000

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 head0.084
GPT teacher head0.347
Teacher spread0.263 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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