Brave spaces: Indigenous children in Canada plan for a different tomorrow
Bibliographic record
Abstract
When considering the impacts of historical trauma and colonization on the lived realities of Indigenous young people within Canada, it is essential that research uses strength-based, capacity-building approaches to ensure that the voices are heard and that their perspectives and advice can be actioned. A series of participatory workshops with adults and children were conducted within urban geographies to explore health-seeking behaviours, health knowledge, and community resiliency. Research took place in Manitoba, Canada (2015–2016, n = 36 girls and 24 adults) with First Nations and Métis community members and British Columbia, Canada (2017, n = 11 children and 15 adults) with Métis community members. Children participated in community transect walks, photo elicitation activities, discussion circles (with adult participant contribution), and projected community mapping exercises where they drew their ideal, imagined community. Community consensus processes were used for member checking as well as initial evaluation of research findings, including the establishment of key themes. Field notes, discussion transcripts, and images were analyzed for similarities and differences between ages, genders, cultural identifiers, and geographies. A key finding was the need for safe spaces that can also be brave spaces, or moments when the community can be free to push for change without reprimand. Children were particularly concerned with sustainable, appropriate housing, safe methods of transportation, access to green spaces, and environmental stewardship within their day-to-day lives. Novelty: Brave spaces are essential for achieving/maintaining wellness within Indigenous communities. This article responds to a need to shift to a determinants of life focus.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".