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Record W4381376931 · doi:10.1080/11926422.2023.2219786

The Russian invasion of Ukraine and humanitarian nationalism in Canada

2023· article· en· W4381376931 on OpenAlexaffabout
Jennifer Hyndman

Bibliographic record

VenueCanadian Foreign Policy Journal · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsYork University
Fundersnot available
KeywordsUkrainianPolitical scienceNationalismFLAGS registerGovernment (linguistics)State (computer science)DiasporaPoliticsLaw

Abstract

fetched live from OpenAlex

Canadian society and governments across multiple jurisdictions have embraced an unprecedented “humanitarian nationalism” in relation to Ukraine and particularly to displaced Ukrainians coming to Canada after the Russian invasion. Humanitarian support for Ukrainians in Canada is salient and unprecedented: Ukrainian flags fly on cars, appear in gardens and are attached to churches, but the Canadian state also champions Ukraine and its people in it foreign policy, and on the federal government website for Ukrainians seeking safety in Canada, where flags are also evident. Comparing recent special government programs for Ukrainians, Afghans and Syrians, data overwhelmingly show more Ukrainians are being helped, support matched by widespread support from civil society. The presence and mobilization of a vast and well-organized Ukrainian diaspora in Canada, as well as the relative absence of securitization concerns in relation to Ukrainians, have shaped the very warm welcome they have received.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.847

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0160.005
Scholarly communication0.0050.001
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.025
GPT teacher head0.290
Teacher spread0.265 · 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

Citations15
Published2023
Admission routes2
Has abstractyes

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