Exploring Continuities Between Family Engagement and Well-Being in Aboriginal Head Start Programs in Canada
Bibliographic record
Abstract
Children and families receive maximum benefits from early childhood programs when families are actively engaged. “Parental involvement” is an established feature of Aboriginal Head Start in Urban and Northern Communities (AHSUNC) in Canada, and there is interest in increasing the knowledge on how AHSUNC sites engage with parents and families. This qualitative study generated knowledge and insights into the nature of family engagement in AHSUNC programs. From May to November 2016, semistructured interviews were undertaken with 26 participants in AHSUNC programs across British Columbia. Participants included parents (n = 10); Elders (n = 6), and AHSUNC program coordinators and family workers (n = 10). Findings illustrate a nuanced, relational, and strengths-based approach to family engagement that included AHSUNC program staff being responsive to the influence of broader social and structural factors on families' everyday lives and program engagement. Findings highlight how family engagement practices in AHSUNC are interdependent and continuous with practices aimed at supporting family well-being. The implications of reframing family engagement from a relational perspective are discussed. These findings have relevancy beyond Indigenous contexts to all early childhood and child health programs that are questioning how to engage with families who experience multifaceted forms of social disadvantage and marginalization.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".