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Record W4417043126 · doi:10.3138/chr-2024-0069

After the Influx: Canadians Respond to World Refugee Year, 1959–60

2025· article· en· W4417043126 on OpenAlexvenueaboutno aff
Marlene Epp

Bibliographic record

VenueCanadian Historical Review · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeGrassrootsImmigrationCivil societyMindsetPoliticsDemocracyPopulation

Abstract

fetched live from OpenAlex

In late 1958, the United Nations General Assembly declared that 1959–60 would be recognized as World Refugee Year (wry). While this came a decade after the influx of the post-Second World War movement of refugees and displaced persons, it was initiated to deal with a growing worldwide refugee crisis, including a lingering population of refugees in Europe. The Canadian Committee for World Refugee Year was established in 1959 to respond to the un-declared special year. This article surveys the activities of wry in Canada, demonstrating that the engagement of Canadians with wry reveals a reluctant federal government, a broadly democratic national endeavour, and a grassroots movement of civil society actors committed to improve the lot of the world’s stateless and homeless. The attitudes of many Canadians as individuals or, represented by non-governmental agencies, as revealed in concrete action, demonstrate the positive role of civil society in social and political action. While some of the activities of wry reflected a condescending and colonialist mindset towards marginalized peoples, they also pointed to an emerging openness on the part of ordinary Canadians to refugee immigrants from across the globe.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.104
Threshold uncertainty score0.752

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.011
Science and technology studies0.0140.007
Scholarly communication0.0060.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.014
GPT teacher head0.267
Teacher spread0.253 · 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 designObservational
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
Published2025
Admission routes2
Has abstractyes

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