MétaCan
Menu
Back to cohort
Record W2183072588 · doi:10.25071/1920-7336.40309

Fear and (In)Security: The Canadian Government’s Response to the Chilean Refugees

2015· article· en· W2183072588 on OpenAlexvenueaboutno aff
Suha Diab

Bibliographic record

VenueRefuge Canada s Journal on Refuge · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical and Social Dynamics in Chile and Latin America
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeGovernment (linguistics)Political scienceIdeologyPoliticsCivil societyRefugee crisisLaw

Abstract

fetched live from OpenAlex

This article examines Canada’s response to the Chilean refugee crisis in 1973. It explores the conditions that made the resettlement of Chilean refugees possible, despite the reluctance of the Canadian government to provide protection for them. The article focuses on the relation between the Canadian overnment’s regulatory discourses and practices on the one hand, and the Canadian public’s contestation of, and challenges to, such discourses and practices on the other. The Chilean refugee crisis revealed that the Canadian refugee protection regime was subject to political ideology, with very little consideration given to the suffering of refugees constructed as a threat to Canadian social, political, and economic well-being. However, civil society played a pivotal role in compelling the government to take a stance toward the refugees, though the government was able to control refugee reception by being deliberately selective about which lives it would save. The visibility and the success of the Canadian public in advocating on behalf of the Chilean refugees demonstrated the potential of this emerging civil power to affect refugee policies and practices while also revealing its limitations.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.132
Threshold uncertainty score0.959

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0330.013
Scholarly communication0.0070.001
Open science0.0010.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.000

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 head0.015
GPT teacher head0.287
Teacher spread0.272 · 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

Citations2
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueRefuge Canada s Journal on RefugeSame topicPolitical and Social Dynamics in Chile and Latin AmericaFrench-language works237,207