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Record W2611600450 · doi:10.1080/09515070.2017.1324760

Latino immigrant parents’ experiences raising young children in the absence of extended family networks in Canada: Implications for counselling

2017· article· en· W2611600450 on OpenAlexaffabout
Mariel Ansion, Noorfarah Merali

Bibliographic record

VenueCounselling Psychology Quarterly · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyLonelinessImmigrationThematic analysisSpouseDevelopmental psychologyPsychological interventionWorryGrandparentQualitative researchSocial psychologySociologyAnxiety

Abstract

fetched live from OpenAlex

Latinos account for 10% of newcomers to Canada, and most are families with young children under the age of 10. In their homelands, Latinos are supported in the parenting process by extended family networks due to the cultural value of familism. Migration to Canada disrupts extended family care-giving, as only one’s spouse and dependent children are allowed to accompany the principal immigration applicant. The purpose of this qualitative study was to explore Latino immigrant parents of young children’s experiences of parenting in Canada in the absence of their extended families, and how they adjust to this new lived reality. An ethnically mixed sample of 10 parents (5 mothers and 5 fathers) participated in semi-structured interviews, which were analysed via thematic analysis. Emerging themes suggested a perceived “uploading” of parental responsibility after migration, producing fear, worry, sadness, loneliness and burnout. These experiences resulted in the negotiation of new parenting partnerships with unanticipated positive outcomes: increased nuclear family cohesion and increased father involvement in childrearing. Parents also described how new support networks were established in surprising ways, such as through interfaces with the health care system. Interventions for facilitating the successful adaptation of Latino parents in a similar predicament are discussed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score0.832

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.344
Teacher spread0.300 · 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 teacher head, 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

Citations17
Published2017
Admission routes2
Has abstractyes

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