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Record W4312126490 · doi:10.30608/hjeas/2022/28/2/8

Success of Jewish Agricultural Colonies in Western Canada

2022· article· en· W4312126490 on OpenAlexaffabout
Eric Wilkinson

Bibliographic record

VenueHungarian Journal of English and American Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsMcGill University
Fundersnot available
KeywordsHuman settlementJudaismSettlement (finance)AgricultureDozenDocumentationRefugeeHistoryEthnologyGeographyPolitical scienceArchaeologyEconomic historyBusiness

Abstract

fetched live from OpenAlex

This article assesses the history of Jewish agricultural settlements created in Western Canada in the late nineteenth and early twentieth centuries. The first settlements were founded following the 1881 Russian pogroms, at which time Canada’s Jewish community tried to resettle refugees in Western Canada. The result was the establishment of over a dozen farming colonies at the turn of the nineteenth and twentieth centuries. By examining the documentation produced by the colonists and the organizations that facilitated their settlement, it is possible to reconstruct the lives of the colonists in each community. This study investigates documents available for twelve different communities that span the Prairies. Settlers report several impediments to their success, including inexperience, poor soil, natural disaster, anti-Semitism, poor administration, and financial hardship. However, the decisive factor which brought an end to the colonies was upward social mobility. They were victims of their own success, unable to maintain their numbers as younger generations moved away, and parents joined them when they retired. The analysis of the farm colonies reveals the causes of their decline and provides grounds for re-evaluating their legacy. (EW)

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0130.003
Scholarly communication0.0030.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.241
Teacher spread0.230 · 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 routes2
Has abstractyes

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Same venueHungarian Journal of English and American StudiesSame topicCanadian Identity and HistoryFrench-language works237,207