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Record W2892440396

Angels of Mercy : Foreign Women in the Anglo-Boer War Ed. 1

2013· book· en· W2892440396 on OpenAlexaboutno aff
Chris Schoeman

Bibliographic record

VenuePenguin Random House South Africa eBooks · 2013
Typebook
Languageen
FieldSocial Sciences
TopicSouth African History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsCourageCompassionAdventureHistoryWorld War IIAncient historyGender studiesArtPolitical scienceSociologyArt historyLawArchaeology
DOInot available

Abstract

fetched live from OpenAlex

After the outbreak of the Anglo-Boer War, hundreds of women left their countries for South Africa, some in search of adventure, others with a strong desire to help the victims of war. They came from all over the world ? from Britain and its colonies, and from pro-Boer countries in Europe. But, whatever their origins, they all came to live and work under harsh conditions in a world that was foreign to them. Angels of Mercy tells the story of twelve of these brave women. Hailing from England, the Netherlands, Belgium, Sweden, Canada, Australia and New Zealand, some worked as nurses on the frontline, while others came to teach Boer children in the concentration camps. Based on personal diaries and letters and other wartime sources, this fascinating and inspiring book tells of their trials and tribulations as they dealt with the dangers of war, the extremes of the environment, and the sad eyes of the dying men under their care. Theirs are stories of compassion and courage.

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)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0180.004

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 head0.020
GPT teacher head0.233
Teacher spread0.213 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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