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Record W7043751208

That memorable campaign: American experiences in the China Relief Expedition during the 1900 Boxer Rebellion

2004· article· en· W7043751208 on OpenAlexaboutno aff

Bibliographic record

VenueCivil War Book Review · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsFirepowerChinaFrontierInfantrySpanish Civil WarQuarter (Canadian coin)CounterattackInsurgencyMilitary tactics
DOInot available

Abstract

fetched live from OpenAlex

At the time of the Boxer Rebellion in China in 1900, the American army was not experienced in dealing with challenges abroad. The Army spent the last quarter of the nineteenth century fighting the Indian Wars in the West and a generation of officers grew to maturity commanding small frontier posts where only a few had the opportunity to maneuver large formations during the Spanish-American War. The infantrymen who marched into Peking in August of 1900 were transitioning between the tactics of the past and the future. The Napoleonic formations used in the American Civil War, already made obsolete at that time by the lethal firepower available, still lingered in the collective memory as the preferred method of maneuvering large bodies of troops and bringing firepower to bear. The Americans who participated in the Boxer Relief Expedition demonstrated impressive adaptability and flexibility. They assembled a sizeable force in China from a scattered military, occupied with fighting an insurgency in the Philippines and garrison duties in the United States. General Chaffee worked within a loosely organized coalition of allied armies in order to rescue the besieged legations in Peking. It is ironic that the Boxer Rebellion, and the international coalition mounted to combat it, was doomed to slip into near obscurity, overshadowed by the military conflagration to come a decade and a half later. The American role in the China Relief Expedition foretold events that would occur in the next major war in the twentieth century, the Great 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.770
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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
Published2004
Admission routes1
Has abstractyes

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