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Record W4211058171 · doi:10.1017/9781108782067.005

Forgotten

2019· book-chapter· en· W4211058171 on OpenAlexaff
Justin Fantauzzo

Bibliographic record

VenueCambridge University Press eBooks · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Chapter 4 examines the idea of the ‘forgotten army’. Whether in the Middle East or Macedonia, soldiers during the war were absolutely certain that their part in the conflict – their suffering, as explored in Chapter 1, and their contribution to the wider war effort, such as the liberation of Palestine or Mesopotamia, as shown in Chapter 3 – had gone unnoticed by the home front. In some ways worse was their fear that those at home had badly misrepresented the war outside the Western Front, recognising the only ‘real’ war as the one being fought in France and Flanders while those in the Middle East and Macedonia were on a ‘picnic’. Again, the Western Front was foremost in the minds of soldiers away from it. This fear became more serious in the war’s final two months, as soldiers in the British Salonika Force (BSF), alongside their French, Greek, and Serbian allies, forced the surrender of Bulgaria, while the Egyptian Expeditionary Force’s (EEF) northwards drive to Aleppo knocked out the Ottomans. In both cases, soldiers in Macedonia and the Middle East argued that it was their campaign that had set in motion the downfall of the Central Powers and, ultimately, the armistice with Germany and an end to the war.

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)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.028
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0090.030
Scholarly communication0.0100.013
Open science0.0020.008
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0280.006

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 head0.021
GPT teacher head0.219
Teacher spread0.199 · 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
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicWorld Wars: History, Literature, and ImpactFrench-language works237,207