Relational approaches to fostering health equity for Indigenous children through early childhood intervention
Bibliographic record
Abstract
This paper reports on key findings of a critical qualitative inquiry undertaken with an Indigenous early child development (ECD) program in Canada, known as the Aboriginal Infant Development Program (AIDP). In depth, semi-structured interviews were used to obtain the perspectives of: Indigenous caregivers and Elders, AIDP workers, and administrative leaders. The findings centre on: (1) a relational perspective of family wellbeing that emphasises the inseparability between child health inequities and the impact of structural social factors on families’ lives, and (2) how AIDP workers’ enact relational accountability to families by: (a) fostering cultural connections; (b) creating networks of belonging and support; (c) responding to caregivers’ self-identified priorities; (d) mitigating racism in healthcare encounters, and (e) deferring an ‘ECD agenda’. Rather than a one-size-fits-all model, these findings illustrate relational approaches to early intervention, characterised by a broader and socially responsive scope of practice and the deferral of a normative ‘ECD agenda’. This study has relevance in a variety of international contexts and to a broad range of disciplines and programs that serve families and children impacted by structural inequities.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| 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".