Indigenous Child Wellness: Measurement Considerations and Assessment Development Guided by a Community Council
Bibliographic record
Abstract
Introduction. There is a need for culturally-aligned wellness measures for Indigenous children, youth and families of turtle island (Canada). Following an identified community need, we co-developed a semi-structured discussion and arts-based measure with the guidance of an Indigenous Community Council. Methods. This study involved 12 adult community members, 11 of whom identify as First Nation and one of whom identifies a Métis. Two members were First Nations Elders. All members of the Council held knowledge related to mental health, wellbeing, social work, traditional knowledge, policy development, and/or Indigenous governance. Indigenous Community Council facilitated small group meetings were conducted online due to social-distancing pandemic requirements to develop a culturally grounded wellness assessment suitable for use with Indigenous children, youth and families. Results. Analyses suggest conversational and arts-based methods to be most culturally relevant in keeping with traditional values of relational wellbeing and storytelling. Additional themes of importance included reciprocity related to providing resources and tangible supports to those who interact with the wellness assessment. Wholism, a limited focus on numeracy, and a strengths-based approach were also revealed to be critical. These results produced the core questions to be used within the wellness assessment created in fulfillment of study aims. Implications and Future Directions. The purpose of the development of this tool is to meet the wellness needs of Indigenous children and families through traditional values and metrics of wellbeing. This approach is used to promote autonomy for Indigenous families by creating a means for understanding wellness developed by Indigenous people, for Indigenous people. The impact of this research will span across community, policy, and practice to contribute to health and wellness sovereignty for Indigenous Peoples in support of intergenerational family thriving.
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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 | 0.050 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".