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Record W4403640911 · doi:10.5787/52-2-1439

The Composition of the Imperial British Forces in the Anglo-Boer War, 1899–1902: A Military and Socio-Historical Overview

2024· article· en· W4403640911 on OpenAlexaboutno aff
L. A. Venter, Marietjie Oelofse, Johan van Zÿl

Bibliographic record

VenueScientia Militaria South African Journal of Military Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAustralian History and Society
Canadian institutionsnot available
Fundersnot available
KeywordsComposition (language)HistoryAncient historyArtLiterature

Abstract

fetched live from OpenAlex

The British forces that served during the Anglo-Boer War (also known as the South African War) of 1899–1902 were an amalgam of several different types of soldiers. These men came from varying geographic and socio-economic backgrounds, and had different reasons for enlisting. This article discusses the composition of the British forces during the war, and adopts a military and socio-historical approach to understand who served in South Africa and why. To this end, the different types of British soldiers are looked at as separate (but ultimately intertwined) groupings, including regular (or career) soldiers, British volunteers, colonial volunteers, and “non-white” combatants. This represents a wide-viewed perspective of the British military system during the late-Victorian era. Keywords: Anglo-Boer War, South African War, British Empire, British Army, British Soldiers, Australian Soldiers, Canadian Soldiers, New Zealand Soldiers

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.617

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.292
Teacher spread0.260 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueScientia Militaria South African Journal of Military StudiesSame topicAustralian History and SocietyFrench-language works237,207