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Record W2500759573 · doi:10.1057/9781137471659_4

E.M. Forster and the War’s Colonial Aspect

2015· book-chapter· en· W2500759573 on OpenAlexaboutno aff
Claire Buck

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2015
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsnot available
Fundersnot available
KeywordsSerbianAncient historyMontenegroFrontierHistoryQuarter (Canadian coin)Spanish Civil WarBulgarianColonialismGermanArtGeographyArchaeology

Abstract

fetched live from OpenAlex

In October 1915, K.E. Royds, a Red Cross Relief worker, sailed through the Strait of Gibraltar and through the Mediterranean to Salonika. Her diary records the African coast, “an unknown world” no more than “a grey outline,” “dim in the morning mist.” “This is really heavenly! But there is nothing to say about it,” notes Royds. 1 On past Algiers seen in moonlight, “an unsubstantial faery thing,” and through Malta’s “narrow streets (some up steps) with overhanging balconies, and Eastern looking shops,” Royds arrives in Salonika and its “Turkish quarter” with “overhanging windows … narrow-latticed shutters … the harems, the gardens green, but enclosed with high walls.” 2 Royds, a war worker, writes while en route to a Greek city occupied by both British and French troops stationed there to support the Serbs in their fight for survival against invasion by German, Austro-Hungarian, and Bulgarian troops. 3 By spring 1916, the infamous Serbian retreat would have seen losses of around 200,000 troops and civilians. 4 Across the Aegean Sea, British, French, Indian, and ANZAC soldiers still fought in the disastrous Gallipoli campaign at the cost of some 250,000 casualties on the Allied side alone. 5 Yet Royds’s production of the exotic and the picturesque comes straight from the writings of Victorian and Edwardian travelers, such as Isabel Burton, Florence Nightingale, or Amelia Edwards. It is not that Royds is either ignorant or nave; she comments in the very same entry on the bad news from the Serbian war zone that “it is hard to realize what is happening north, above the hills.” 6 Neither is she atypical. For Royds and many others, whether soldiers or non-combatants, the war was an opportunity to travel on the edges of Europe’s borders and beyond. 7 These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.009
Scholarly communication0.0070.006
Open science0.0010.006
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0220.004

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 head0.028
GPT teacher head0.270
Teacher spread0.242 · 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 designTheoretical or conceptual
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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