The Development of the First Nations Children Wellbeing Measure
Bibliographic record
Abstract
Objectives: The overall goal of this project was to implement a measurement tool intended to assess the wellbeing of First Nations children within the Robinson Superior Treaty Area. Methods: A community-based participatory research approach was utilized, which included a research advisory composed to employees from the organization that was partnered with. Both interviews and focus groups were held with members of the communities within the Robinson Superior Treaty Area, and the content of these was examined to determine indicators of wellbeing for children in these communities. The indicators that arose from this analysis made up the pilot version of the measure, which was administered to the parents or caregivers of children (n = 91) who were seen through the intake service for the organization. They were also administered the Child and Adolescent Needs and Strengths measure (Lyons et al., 1999). Results: A principal components analysis was performed, which yielded three factors: (1) General Wellbeing, (2) Traditional Activities, and (3) Social Engagement. Discussion: Involvement in traditional activities and engagement in culture were cited as fundamental indicators of wellbeing of First Nations children, which is consistent with the majority of the literature. The instrument that was created and evaluated represents one of few valid tools available to assess this. Implications: The measure and process of creating this measure contributes to the literature on the significance of traditional activities for the wellbeing of Indigenous people.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".