Nurturing roots: Motivations of Inuit foster parents caring for Inuit children in Nunavik
Bibliographic record
Abstract
BACKGROUND: Indigenous children are overrepresented in the child protection system in Canada, particularly in Nunavik, Quebec, where Inuit children face significant risks of being placed outside their communities. Previous studies have often centered on service providers or the perspectives of non-Indigenous foster families, neglecting the voices of Inuit foster parents themselves. OBJECTIVE: This study explored the motivations and experiences of Inuit foster parents in Nunavik for becoming and remaining foster parents, as well as factors that could lead to a cessation of care provision. PARTICIPANTS AND METHODS: Fifteen Inuit foster parents (12 women, 3 men) from various communities in Nunavik participated in semi-structured interviews. Interviews were analyzed using inductive thematic analysis. RESULTS: Key motivations for fostering included keeping children within the family, preserving cultural identity, and respecting the child's preferences. Foster parents reported significant challenges, including a lack of support from child protection services and dealing with trauma. CONCLUSIONS: The study highlights the critical role of Inuit foster parents in maintaining cultural continuity for Inuit children and underscores the need for supportive policies and practices that recognize their motivations and values. Enhanced support and culturally sensitive approaches are essential to improve the recruitment and retention of Inuit foster parents.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".