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Record W4394948700 · doi:10.25071/2561-5467.1131

Fleet Carrier in Name or Fact?: The Post-War Misinterpretation of USS Ranger as Unsuitable for Combat in the Pacific

2024· article· en· W4394948700 on OpenAlexvenueno aff
James Alvey

Bibliographic record

VenueThe Northern Mariner / Le marin du nord · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesHistoryArtEthnologyLibrary scienceComputer science

Abstract

fetched live from OpenAlex

Since World War Two, the USS Ranger (CV-4) has become perceived as incapable of combat in the Pacific Theater. Digitization has provided a new opportunity to examine its perception by commanders responsible for the carrier’s employment. These records reveal that the common perception of the carrier stemmed from diplomatic necessity, from an overworked bureau uneager for additional projects, and from commands eager to acquire Ranger for non-combat duty. Ranger was considered by the US Navy as fit for combat in the Pacific Theater during WWII, but other requirements overrode the need for one additional combatant carrier in the Pacific.
 À la suite de la Seconde Guerre mondiale, l’USS Ranger(CV-4) était considéré comme un porte-avions incapable de combattre dans le théâtre du Pacifique. La numérisation a permis aux commandants responsables de l’emploi du porte-avions d’examiner cette perception sous un nouvel angle. Ces documents révèlent que la perception commune du porte-avions provenait de la nécessité diplomatique, d’un bureau surchargé de travail qui voulait éviter des projets supplémentaires et de commandements désireux d’acquérir le Ranger pour des tâches non combattantes. La marine américaine considérait le Ranger comme étant apte au combat dans le théâtre du Pacifique pendant la Seconde Guerre mondiale, mais d’autres exigences l’ont emporté sur la nécessité d’avoir un porte-avions de combat supplémentaire dans le Pacifique.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.908

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.277
Teacher spread0.258 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

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