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Record W4254091253 · doi:10.32920/ryerson.14647200

Failed Refugee Claimants: Negotiating Rights, Security and Citizenship

2021· preprint· en· W4254091253 on OpenAlexaboutno aff
Athanas Njeru

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeCitizenshipNegotiationPolitical scienceMoral panicGovernment (linguistics)ImmigrationSociologyLawCriminologyGender studiesPolitics

Abstract

fetched live from OpenAlex

Individuals and groups engage discursively in relationships and negotiations as they try to structure and influence the social space where they live. This engagement further constructs the social space through the use of concepts, objects and subject positions. This study examines the representation and construction of failed refugee claimants by the Canadian newsprint media. Through the use of the moral panic as envisioned by Stephen Cohen and others, the study employs critical discourse analysis to reveal complex struggles in the Canadian refugee system through the discursive activity of the government, nonprofit agencies and social networks. The study concludes that a moral panic has occurred in the Canadian refugee system and has resulted in the enactment of a new Canadian refugee system through the passing of the Balanced Refugee Reform Act Bill C-11), Protecting Canada’s Immigration Act (Bill C-31) and the Faster Removal of Foreign Criminals Act (Bill C-43).

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)0.008
metaresearch head score (Gemma)0.017
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 score0.530
Threshold uncertainty score0.946

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0350.065
Scholarly communication0.0210.008
Open science0.0030.013
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0060.000

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 head0.021
GPT teacher head0.304
Teacher spread0.283 · 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
Published2021
Admission routes1
Has abstractyes

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