Every child matters: An imperative paediatric healthcare movement
Bibliographic record
Abstract
Guided by the 2015 Truth and Reconciliation Commission Report, this paper examines the legacy of colonialism in Canada and its continued detrimental effects on the health of First Nations, Inuit, and Métis children. Supporting Call to Action 24, which emphasizes the importance of Indigenous health and histories within medical training, the "Every Child Matters" social movement can inform the domains of education, patient care, non-Indigenous advocacy, and Indigenous inclusion, drawing attention to the negative impacts of Canadian institutions, including residential schools, on Indigenous peoples. This paper argues that "Every Child Matters" can provide a novel conceptual framework within which non-Indigenous paediatric health practitioners may engage in self-reflection, practise cultural humility, and deliver trauma-informed care with the aim of decolonizing their practices and supporting equitable healthcare for Indigenous children. Additionally, this proposed framework can support efforts toward reconciliation, providing opportunities for meaningful partnerships with Indigenous patients, families, and colleagues.
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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 | 0.018 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.038 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.008 | 0.017 |
| 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".