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The Ukrainian “Galicia” Division: From Familiar to Unexplored Avenues of Research

2019· article· en· W2996864604 on OpenAlexaffabout
Myroslav Shkandrij

Bibliographic record

VenueKyiv-Mohyla Humanities Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean history and politics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsUkrainianSurrenderNarrativeMemoirSpanish Civil WarPoliticsCommissionHistoryPolitical scienceDivision (mathematics)LawSociologyMedia studiesLiteratureArtPhilosophy

Abstract

fetched live from OpenAlex

This article examines the main narratives that have dominated scholarly and political writings on the “Galicia” Division, the Waffen-SS 14th Grenadier Division that at the end of the Second World War was renamed the 1st Ukrainian Division of the Ukrainian National Army. Dominant narratives have focused on accusations of criminality, the hope that the formation would serve as the core of a national army at the war’s end, survival as a motivation for signing up, the experience of the soldiers after their surrender to the British, and the decision to transfer former soldiers to the UK and then to give them civilian status. Only the first of these narratives has been explored in depth as a result of the 1986 Deschиnes Commission of Enquiry into War Crimes in Canada and the 1989 Hetherington-Chalmers Report in the UK. Far less attention has been devoted to other narratives, and some lines of enquiry suggested by the rich memoir and creative literature have hardly as yet been touched.

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)0.004
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0080.023
Scholarly communication0.0120.012
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.149
GPT teacher head0.390
Teacher spread0.241 · 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
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
Published2019
Admission routes2
Has abstractyes

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