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The Pacific Borderlands in Wartime

2022· book-chapter· en· W4391084176 on OpenAlexaboutno aff
Andrea Geiger

Bibliographic record

VenueUniversity of North Carolina Press eBooks · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAsian American and Pacific Histories
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationPacific RimGeographyWorld War IIGovernment (linguistics)Political scienceEconomic historyHistoryOceanographyArchaeology

Abstract

fetched live from OpenAlex

As World War II approached, the mobility of Japanese immigrant fishers gave rise to ever more strident allegations of smuggling and spying in both Canada and the US. Along the Alaska coast, reported intrusions into US waters by Japanese fishing vessels were depicted as the vanguard of a coming invasion. The growing pressure Japan brought to bear along the North Pacific coast, reflected in ongoing disputes over oceangoing fisheries and the pelagic sealing industry, combined with Japan’s resentment of the race-based exclusion and unequal treatment of Japanese immigrants by both the United States and Canada, heightened tensions among all three nations. Canada and the United States forcibly removed people of Japanese ancestry from the Pacific coast and interned or incarcerated them during World War II. Alaska Natives with a Japanese forebear were among those forcibly uprooted. Chapter 5 also addresses the forced relocation of the Aleut by the US government, as well as that of the Aleut taken prisoner by the Japanese Imperial Army during the Aleutian campaign and taken to Japan. Japanese Canadians were forced to choose between moving east or being repatriated or expatriated to Japan and were not permitted to return to the B.C. coast until 1949.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.003
Scholarly communication0.0050.003
Open science0.0000.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0170.002

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 head0.015
GPT teacher head0.209
Teacher spread0.194 · 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
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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