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Record W4384695921 · doi:10.25071/2561-5467.1073

Edward J. Marolda, Admirals Under Fire. The US Navy and the Vietnam War by Greg Swinden

2023· article· en· W4384695921 on OpenAlexvenueno aff
Greg Swinden

Bibliographic record

VenueThe Northern Mariner / Le marin du nord · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNavyVietnam WarHistoryAeronauticsArt historyAncient historyEngineeringArchaeology

Abstract

fetched live from OpenAlex

A Vietnam War veteran himself, Edward Marolda has produced an excellent analysis of the US Navy during that war, as seen through the lens of the five Chiefs of Naval Operations (CNO) who led the navy from 1958 to 1978, and thus, encompassing the entire period of the conflict from its most early days to the very bitter end.Admiral's Harry Felt, Ulysses Sharp, Thomas Moorer, Elmo Zumwalt and James Holloway each undertook four year terms as the CNO.Their service also corresponded closely with the terms of Presidents Eisenhower, Kennedy, Johnson, Nixon, Ford and Carter.The naval-political relationship was often very difficult -hence the title of the book.Marolda's in-depth analysis of the US Navy's roles and tasks during the war stretches chronologically from the grand strategic to the tactical and provides a candid view of each admiral's strengths and weaknesses.Felt and Sharp appear too stuck in a Second World War/Korean War view of the world and the way the war should be fought.Moorer was more realistic, seeing Vietnam as a side show, with the real threat being the rise of Soviet naval power, but he was also focused on becoming the Chairman of the Joint Chiefs of Staff.Zumwalt also saw the growth of the Russian Navy as more important than Vietnam and sought to improve ship numbers and capability.This was a difficult task with funding shortages meaning many elderly vessels were retained and shipbuilding reduced.Zumwalt also undertook several reforms to improve discipline, in the face of increased drug usage in the US Navy, as well improving morale and retention of junior personnel -particularly among minority personnel, such as African-Americans, Hispanics and women.His Z-Grams to the fleet became famous (and in some cases, infamous) and alienated him from many within the Navy's leadership.In 1974 Holloway inherited a navy struggling for numbers of effective ships and personnel; but he saw the method in some of Zumwalt's perceived madness and modified the reforms, which later saw increased

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)0.002
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: Review · Consensus signal: none
Teacher disagreement score0.074
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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
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
Published2023
Admission routes1
Has abstractyes

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