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Record W1838576113 · doi:10.14288/bcs.v0i87.1364

A Tale of Two Cities: The Reception of Japanese Evacuees in Kelowna and Kaslo, B.C.

2010· article· en· W1838576113 on OpenAlexaboutno aff
Patricia E. Roy

Bibliographic record

VenueOpen Collections · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)PopulationGeographyTable (database)DemographyArchaeologySociology

Abstract

fetched live from OpenAlex

This is a tale of two British Columbia interior cities which, despite similarities in their backgrounds, had very different reactions to the arrival of Japanese evacuees in 1942. Both Kelowna and Kaslo were service centres for the surrounding countryside. In both cities the population was overwhelmingly British in origin ; in both, about a third of the people adhered to the United Church of Canada and about a quarter to the Church of England. Except for the Roman Catholics, who formed about 20 per cent of Kelowna's population, no other denomination claimed more than 10 per cent of the population (table 1). As the crow flies, only about 125 miles separate the cities, but the Selkirk and Monashee mountains are so formidable that no direct road or rail line links them. Indeed, more than mountains separated Kelowna and Kaslo. Kelowna and Kaslo were not the only British Columbia communities to receive Japanese evacuees, but their very different responses illustrate two extremes. Kelowna, which had a population of 5,118 in 1941, is situated in the

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)0.001
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 score0.419
Threshold uncertainty score0.843

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0350.006
Scholarly communication0.0050.002
Open science0.0010.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.276
Teacher spread0.262 · 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

Citations5
Published2010
Admission routes1
Has abstractyes

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