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Record W4238167223 · doi:10.32920/14656572

"A Stone In The Ocean": A Mixed Methods Investigation Into The Experiences Of Families Trying To Reunite In Canada

2021· preprint· en· W4238167223 on OpenAlexaffabout
Beth J. Martin

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicResearch in Social Sciences
Canadian institutionsCarleton UniversityToronto Metropolitan UniversityMcGill University
Fundersnot available
KeywordsImmigrationIntersectionalityFamily reunificationSociologyPoliticsPolitical scienceFocus groupPublic relationsGender studiesCriminologyLaw

Abstract

fetched live from OpenAlex

Every year many families are formed, or find themselves separated, across borders. To address the problem of family separation, the family class stream of immigration to Canada, which accounts for 20-30% of new immigrants annually, allows citizens or permanent residents to sponsor certain family members for permanent residency. Yet there has been very little research on experiences of this policy. Family reunification immigration, located at the intersection of the personal and the political, has been marginalized by masculinized policy disciplines that focus on macro-trends in immigration and render the family invisible, and by feminized disciplines that focus on the family and individual in immigration while rendering policy invisible. This dissertation fills that gap in the literature, using a critical policy studies approach informed by aspects of Critical Theory, intersectionality and Foucauldian interpretations of power. I explore the lived experiences of families as they apply to reunite through the family class stream, and of families who would like to apply to reunite but cannot. I used mixed methods—qualitative interviews and quantitative surveys—to collect data from 169 families, and 100 key informants who support applicant families, including lawyers, consultants, settlement workers and constituency office caseworkers. This approach and research design allowed me to expose and develop a deep knowledge of families’ experiences that have until now been marginalized. Findings show that, though the decision on an immigration application is important, a sole focus on that decision both excludes applicants’ vastly different experiences during the process and renders invisible those who cannot even apply. Diversity in experiences was closely related to interactions between different aspects of social location, and policy design and implementation. Applicants exercised many forms of initiative and agency, but were ultimately constrained by policy structures. The new Government has recently made promising changes, but we must ensure these changes are effective and continue to advocate for further improvements that would mitigate applicants’ negative experiences. Finally, more research needs to be done, most importantly on family reunification through immigration streams that were excluded from this study.

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)0.015
metaresearch head score (Gemma)0.023
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 score0.119
Threshold uncertainty score0.557

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.005
Science and technology studies0.0490.019
Scholarly communication0.0100.005
Open science0.0050.010
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.097
GPT teacher head0.447
Teacher spread0.350 · 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
Published2021
Admission routes2
Has abstractyes

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