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Record W1574544308

The Combat Soldier: Infantry Tactics and Cohesion in the Twentieth and Twenty-First Centuries

2015· article· en· W1574544308 on OpenAlexaboutno aff
George J. Woods

Bibliographic record

VenueThe US Army War College Quarterly Parameters · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsInfantryBattlePoliticsLawSociologyMedia studiesPolitical scienceHistoryAncient history
DOInot available

Abstract

fetched live from OpenAlex

Combat Soldier: Infantry Tactics and Cohesion in the Twentieth and Twenty-First Centuries By Anthony King Oxford, UK: Oxford University Press, 2013 538 pages $107.00 [ILLUSTRATION OMITTED] After more than a decade of continuous conflict, Anthony King, a Cambridge graduate and professor of sociology at Exeter University, authored a superb and in-depth look at today's soldiers. King's research passion, the examination of the sociological phenomenon collective action--how and why groups form and sustain themselves--ranges from sports teams to the military. In Combat Soldier, Kang meticulously explores how cohesion and combat performance, often assumed unchanging and universal across wars, may have changed in the course of the last century, as armies have moved away from the citizen towards the all-volunteer professional model. King examines how armies in Western-like, democratic societies behave and maintain cohesion in the face of the hellish experience of combat. He does so by deftly analyzing how the multiplicity of factors including comradeship, political motivation, doctrine, tactics, and training (39) affected combat performance in battle from World War I to the present. Rather than a macro perspective, he studies the phenomenon from the grassroots level using the infantry platoon as his unit of analysis to identify what motivates these soldiers to act in unison in a combat environment. His method includes comparing citizen army platoons from World War I to Vietnam against the modern, professional army platoons which have fought from the Falklands to the most recent operations in Afghanistan. By design, his emphasis focuses on six armies: Australia; Canada; France; Germany; the United Kingdom; and the United States, and applicable infantry platoons from their marine ground units. Precise definitions and disciplined social science methodologies aid King's objectivity in analyzing the conditions affecting combat performance. Consequently, he challenges commonly held notions of citizen armies, both positive and negative, in comparing their performance across countries and wars to make his findings more comparable and generalizable. S.L.A. Marshall's research based on 30 years of study on combat soldiers serves as King's starting point. Marshall, widely regarded as the expert on soldiers in combat, came under attack over the past 25 years. Criticisms cast doubt on his methodology and objectivity, discrediting the findings in his seminal work, Men against Fire. While addressing criticisms of Marshall's research, King examines and defends the essence of Marshall's surprising and controversial findings--one in four combat soldiers actually fired weapons in battle. In the chapter, The Marshall Effect, King reestablishes the efficacy of Marshall's work and uses it to serve as his foundation for exploring the differences in combat performance between citizen armies of the twentieth century and professional armies of the current century. King explains how armies formerly appealed to masculine honour, nationalism, ethnicity and patriotic duty (97) to inspire soldiers to fight in the citizen armies of the 20th century. However, he argues new factors have emerged, as a result of the shift from mass to modern tactics due largely to advances in technology and the changing nature of modern warfare. Such factors account for significant increases in the effectiveness of today's combat soldier--a direct result of the shift to all-volunteer, professionalized armies. …

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.999

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.260
Teacher spread0.237 · 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 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
Published2015
Admission routes1
Has abstractyes

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