Immigrant Mothers' Experiences With Child Soothing in Vancouver, Canada: ‘I Just Want to Be a Good Mom’
Bibliographic record
Abstract
BACKGROUND: Parental soothing resources can increase parents' confidence in practicing safe soothing techniques. However, there is a dearth of resources that help immigrant parents gain confidence. Understanding the soothing experiences of immigrant mothers can provide important insight into how to develop culturally sensitive soothing resources for them. In this study, we addressed the question, 'What are immigrant mothers' experiences with child soothing in Vancouver, Canada?' METHODS: We used tenets of post-structural feminist theory and feminist methodologies to inform our approach and conducted three focus groups with 23 mothers who had at least one child aged 0-5 years. RESULTS: Two discourses were identified through a critical discourse analysis: (a) feminising care: gendered mothering ideals can isolate immigrant mothers and (b) cultural silencing: dominant cultural ideals for soothing can subjugate non-conformative practices. CONCLUSIONS: Societal pressures on women to soothe children can elicit feelings of isolation, sadness and concern for immigrant mothers, who can lack social supports and may not feel capable of subscribing to culturally idealised practices. Findings can be used to inform the cultural competency of injury prevention resource development to address unique cultural and gender-sensitive needs of immigrant mothers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".