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Record W1976262307 · doi:10.5860/choice.41-1773

Stepping stones to nowhere: the Aleutian Islands, Alaska, and American military strategy, 1867-1945

2003· article· en· W1976262307 on OpenAlexaboutno aff

Bibliographic record

VenueChoice Reviews Online · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicAsian American and Pacific Histories
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryGeographyAncient historyGenealogy

Abstract

fetched live from OpenAlex

The Aleutian Islands, a mostly forgotten portion of the United States on the southwest coast of Alaska, have often assumed a key role in American military strategy. W.H. Seward, the US secretary of state who brokered the purchase of Alaska, believed that the acquisition would permit the United States to dominate the Pacific. In the 1990s, Bill Clinton attempted to install an American ballistic missile defence system on the islands. But for most Americans, prior to the Second World War, the bleak and barren islands were of far less interest than the Philippines. In Stepping Stones to Nowhere, Galen Perras shows how that changed with the Japanese occupation of the western Aleutians, which climaxed in the horrendous battle for Attu. Efforts to make the area a major theatre of war rivalling Europe or the South Pacific foundered, but certainly not for lack of effort. The campaign was unique in its involvement of Britain, the Soviet Union, and Canada. Perras reveals how this clash in the North Pacific demonstrated serious problems with the way that American civilian and military decision makers sought to incite a global conflict. Thoroughly researched and accessible, this book will be invaluable to military and naval historians as well as those with a general interest in the history of the Second World 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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.919
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.036
GPT teacher head0.344
Teacher spread0.308 · 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

Citations8
Published2003
Admission routes1
Has abstractyes

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