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Record W2765677200 · doi:10.1017/s0080440117000111

GLOBALISING AND LOCALISING THE GREAT WAR

2017· article· en· W2765677200 on OpenAlexaboutno aff
Adrian Gregory

Bibliographic record

VenueTransactions of the Royal Historical Society · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsnot available
FundersArts and Humanities Research Council
KeywordsNova scotiaNarrativePalestineHistoryFirst world warFocus (optics)Spanish Civil WarWorld War IIPolitical scienceGenealogyAncient historyEthnologyLiteratureArchaeologyArt

Abstract

fetched live from OpenAlex

ABSTRACT This article is intended to suggest an approach to the global history of the First World War that can provide a method of managing the potentially unwieldy concept of global conflict by understanding it through the war's impact on localities. By concentrating on four relatively small but significant cities; Oxford in England, Halifax in Nova Scotia, Jerusalem in Palestine and Verdun in eastern France, which experienced the war in very different ways, it looks at both the movement of people and things and the symbolic interconnectivities that made the war a ‘world war’. This local focus helps challenge both the primacy of self-contained national history and the focus on the violent interaction of the opposing sides which are the more normal ways of narrating the war. It does not deny the usefulness of these traditional structures of narration and explanation but suggests that there are different and complementary ways the war can be viewed, which create different emphasis and chronologies.

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 score0.012
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.022
Scholarly communication0.0090.004
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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
Published2017
Admission routes1
Has abstractyes

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Same venueTransactions of the Royal Historical SocietySame topicWorld Wars: History, Literature, and ImpactFrench-language works237,207