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Record W2994023442

A Causal Model of Warfare

2001· article· en· W2994023442 on OpenAlexaboutno aff
Alan D. Zimm

Bibliographic record

VenueMilitary review · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsVictoryAdversaryLawPower (physics)Decisive victorySociologyLaw and economicsComputer securityPolitical sciencePoliticsComputer science
DOInot available

Abstract

fetched live from OpenAlex

Regardless of whether its mechanism is or warfare, military victory often depends on intangibles such as morale and will to fight Zimm crafts a model to explain how warfare targets those intangibles and triggers psychological results that are more decisive than physical ones. CURRENT US MARINE Corps doctrine dating from 1989 issue of Fleet Marine Force Manual 1, Warfighting, espouses warfare.' Maneuver shatters the cohesion of system, achieving victory by paralyzing an enemy who has lost ability to resist. 2 This concept identifies as a weapon. The US Army concept of is less ambitious. Maneuver is relative to to put him at a disadvantage, wherein friendly forces gain ability to destroy or hinder his movement through direct or indirect application of lethal power or threat thereof.3 Victory is achieved through applying overwhelming combat power. These two contrasting concepts have been labeled as maneuver versus attrition or schools; merits of each have been extensively debated.4 Supporters cite historical examples in which their system of warfare resulted in victory. However, of outcome does not imply a similarity of process.' Military theorists struggle with a chicken and egg conundrum: destruction can cause panic and paralysis, and panic and paralysis facilitate destruction. Which is primary path to victory? On Victory History suggests that there are indeed two mechanisms-physical and moral-of victory: destroying or incapacitating opponent physically and destroying his will. In physical mechanism of victory, defeated side is annihilated. Cannae, Thermopylae, Fetterman massacre, Little Big Horn, Iwo Jima and Isandhlwana are examples. But in vast reach of history, examples of annihilation are mercifully few. Such battles are stuff of epics, and like epics, they are rare. Soldiers rarely fight to last man. Characteristically, they surrender, retreat or run in panic well before extermination. At Waterloo, French Army collapsed after Imperial Guard failed to break British line. Destruction had been widespread; French had already suffered about 15,000 casualties. But defeat came when remaining 60,000 no longer had will to stand. Some have noted that destruction and death are primary mechanisms to undermine morale and have concluded that firepower is sufficient for victory. But physical destruction is not only way to influence morale. While there are examples of resolving battles by annihilating physically, there are more examples of battles being resolved purely by destroying enemy's morale and will to fight During English King Henry V's campaign in France, [w]hen fall of Rouen became known, rest of Normandy quickly submitted. Often it was sufficient for Henry's captains to appear in front of a town or a castle for it to surrender.6 During War of Spanish Succession, many fortresses and fortified towns surrendered without a fight after Duke of Marlborough's spectacular victory at Ramillies.7 At sea it was common for warships to surrender to a more powerful opponent without exchanging a shot; confrontations were resolved with only threat of destruction. Perhaps most curious example of purely moral mechanism of victory is case of capitulating a full field army. At onset of War of 1812, Brigadier General William Hull ... withdrew to village of Detroit on 11 August Five days later, Major General Isaac Brock, British commander in Upper Canada, moved on Detroit with a much smaller force of regulars, militia and Indians. In a colossal bluff, he urged Hull to surrender, explaining that, once fighting commenced, he would be unable to control his Indians and a massacre might result. …

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)0.003
metaresearch head score (Gemma)0.007
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.005
Scholarly communication0.0040.007
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0380.003

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 head0.081
GPT teacher head0.334
Teacher spread0.252 · 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

Citations1
Published2001
Admission routes1
Has abstractyes

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