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Record W2486790301 · doi:10.14288/1.0103570

The everyday experiences of a north coast Japanese-Canadian fisherman, at home and in the workplace

2013· article· en· W2486790301 on OpenAlexaboutno aff
Justin Staeck

Bibliographic record

VenuecIRcle (University of British Columbia) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicResearch in Social Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyHistory

Abstract

fetched live from OpenAlex

For many years before World War II, the Japanese workmen at North Pacific Cannery in Port Edward, BC, were subject to what was believed to be racial discrimination based on unfair economic competitiveness. By focusing on different aspects of the lives of Japanese workmen at NPC, this historical narrative aims to fill some of the gaps still existent in Japanese-­‐Canadian history. The essential experience and direction that was transferred from Japanese fishermen to the fishing industry was unmatched yet with it came little respect and acknowledgment rooted in social, political, and economic reasons. Some scholars have emphasized the roots of Canadian discrimination against the Japanese were sewn out of the Japanese’s’ own economic competitiveness in a place that was then referred to as a ‘white man’s province’. This argument is misleading and, after undertaking archival and oral history research, it has since shown that what first began as anger towards Japanese immigrants born of economic aggression very quickly shifted towards hostility entirely based on racial prejudice.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0390.016
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.213
Teacher spread0.200 · 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 designQualitative
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
Published2013
Admission routes1
Has abstractyes

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