Examining the Adaptation of Parenting Practices During Acculturation of Yoruba Immigrants in Canada: The Sociocultural Models Approach
Bibliographic record
Abstract
Abstract: This study addressed some of the regularities and mechanisms of the acculturation of Yoruba immigrant parents in Canada. Guided by the theory of sociocultural models (TSCM) (Chirkov, 2020; 2022; 2025), the research questions were: What are the Yoruba and Euro-Canadian sociocultural models (SCMs) of parenting, and how do immigrants perceive them? How do Yoruba immigrant parents negotiate these two sets of models? How is each model reflected in the socialization goals and disciplinary practices these parents apply to their parenting in the Canadian context? Researchers interviewed five parents and analyzed them using theory-driven and open coding. The study identified an explicit acculturation gap between two sets of SCMs. The majority of the parents were aware of this discrepancy. The primary challenge for the participants was the lack of communal support and guidance for parenting. They were eager to reflect on their home parenting models and accept some elements of the Euro-Canadian modes. They held on to the Yoruba values and socialization goals but were attentive to and ready to adapt to normative Canadian disciplinary practices. The authors have suggested creating a program for immigrant parents to help them adjust their parenting models and parental behavior to fit their new cultural environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".