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Record W2202544340 · doi:10.1353/ces.2015.0039

The Ukrainian Canadian Chaplaincy during World War Two

2015· article· en· W2202544340 on OpenAlexvenueaboutno aff
Roman Yereniuk

Bibliographic record

VenueCanadian ethnic studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary, Security, and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianWorld War IIPolitical scienceWork (physics)First world warLawHistoryAncient historyEngineering

Abstract

fetched live from OpenAlex

This paper discusses the creation, development, and significance of the office of Ukrainian chaplaincy in the Canadian military forces during World War II. Seven Ukrainian chaplains—three from the Ukrainian Catholic Church of Canada and four from the Ukrainian Orthodox Church of Canada—served the approximately 32,000–35,000 military personnel. Of these, three chaplains served in England and two in Europe. The work of the chaplains is discussed as is the role of their superiors in Canada and abroad. The paper evaluates the significance of the Ukrainian chaplaincy in the military effort, as well as in the development of the post-WWII Ukrainian Canadian community. Cet article présente la création, le développement et l’importance du bureau de l’aumônerie ukrainienne dans les forces militaires canadiennes pendant la seconde guerre mondiale. Sept aumôniers ukrainiens – appartenant aux Églises ukrainiennes du Canada, dont trois catholiques et quatre orthodoxes – ont œuvré auprès d’environ 32,000–35,000 officiers et soldats. Parmi eux, trois ont servi en Angleterre et deux sur le continent européen. Nous étudions ici le travail de ces aumôniers, ainsi que le rôle de leurs supérieurs au Canada et outremer. Nous y évaluons aussi l’importance du rôle de l’aumônerie ukrainienne dans l’effort militaire, ainsi que dans le développement de la communauté canadienne ukrainienne d’après la seconde guerre mondiale.

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 score0.042
Threshold uncertainty score0.303

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0160.003
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.203
GPT teacher head0.414
Teacher spread0.211 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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