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Transnationalizing Families: Canadian Immigration Policy and the Spatial Fragmentation of Care‐giving among Latin American Newcomers <sup>1</sup>

2008· article· en· W2105409746 on OpenAlexaffabout
Judith K. Bernhard, Patricia Landolt, Luin Goldring

Bibliographic record

VenueInternational Migration · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsYork UniversityUniversity of TorontoToronto Metropolitan University
Fundersnot available
KeywordsImmigrationLatin AmericansNormativeFamily reunificationImmigration policyShameBiological dispersalPolitical scienceSociologyContext (archaeology)Settlement (finance)Demographic economicsGender studiesGeographyDemographyPopulationEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract Complex factors associated with migration and immigration policies contribute to the dispersion of families across space. We draw on interviews with 40 Latin American women in Toronto who experienced separation from children as a result of migration and argue that Canadian immigration policy and elements of the women’s context of departure lead to the systemic production of transnational family arrangements. Once in Canada, the women dealt with unexpected lengths of separation, the spatial dispersal of social reproduction, and post‐reunification problems. The absence of a normative framework that could help the mothers make sense of family dispersal meant that their experiences of migration, family separation, reunification and settlement were marked by tension, guilt, isolation and shame.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.413

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 studies0.0190.009
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.001
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 head0.009
GPT teacher head0.270
Teacher spread0.261 · 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

Citations93
Published2008
Admission routes2
Has abstractyes

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