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Record W2912078009 · doi:10.1080/01419870.2019.1569703

Diaspora mobilization and the Ukraine crisis: old traumas and new strategies

2019· article· en· W2912078009 on OpenAlex
Milana Nikolko

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEthnic and Racial Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsCarleton University
FundersJohns Hopkins University
KeywordsDiasporaUkrainianMemorializationNarrativeMobilizationPolitical scienceFamineInterpretation (philosophy)SociologyState (computer science)Identity (music)Gender studiesPolitical economyLawAesthetics

Abstract

fetched live from OpenAlex

This article presents an analysis of mobilization strategies among Ukrainian diaspora groups in Canada in their response to the Ukrainian crisis of 2014–15. By mapping recent Ukrainian diaspora activism, the purpose of this article is to understand international non-state actor influence on transitional justice during crisis. The first part draws on studies of traumatic memories and the role they play in developing a victim-based identity among a diaspora. Practices of memorialization of the famine 1932–33 in Ukraine were created through emotional causal mechanisms that captured traumatic emotions on paper in the diaspora, creating narratives that were further sustained through value-based mechanisms. The second part explains how the diaspora bridged its interpretation of traumatic memories with the home country. The last part demonstrates how existing narratives and discourses were utilized through a strategic causal mechanism to create a rapid response among Ukrainian Canadians to the crisis in Ukraine.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.472
Threshold uncertainty score0.832

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.321
Teacher spread0.275 · 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