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Record W4283723835 · doi:10.1111/cag.12784

Contrapuntal histories of war resistance: Mapping US war resister migrations, questioning Canada as safe haven

2022· article· en· W4283723835 on OpenAlexafffundvenueabout
Alison Mountz, Jacque Micieli‐Voutsinas, Shiva S. Mohan

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsUniversity of Northern British ColumbiaWilfrid Laurier UniversityBalsillie School of International Affairs
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGeopoliticsMilitarismHavenSpanish Civil WarArgument (complex analysis)Political scienceSafe havenResistance (ecology)Political economySociologyPoliticsHistoryEconomic historyLaw

Abstract

fetched live from OpenAlex

This paper frames two generations of war resister migration from the United States to Canada and the social movements that supported them as contrapuntal histories, disparate yet woven together, and entangled across space and time. We argue that Canada has functioned at key historical moments as safe haven for war resisters from and others fleeing conflict led by the United States, but that this role was always provisional, historically contingent, and never guaranteed. It is therefore crucial to understand the social movements that arose to support the search for safe haven at different points in geopolitical relations and histories. We develop this argument with empirical research about people who migrated to Canada during wars led by the United States in Vietnam, Iraq, and Afghanistan. In documenting both generations of resister migration, we move across scales to understand the highly embodied geopolitics of these journeys, which run parallel and diverge in key ways. Our analysis thus maps the shifting history of Canada as a safe haven for those seeking refuge from the violence of war and militarism in the United States.

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.302

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0130.008
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.001
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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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

Citations1
Published2022
Admission routes4
Has abstractyes

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