Engaging youth to promote their well-being: methods and findings from a knowledge mobilization project in Nova Scotia, Canada
Bibliographic record
Abstract
The United Nations Convention on the Rights of the Child affirms the human right of children to have their voices heard about issues affecting their lives. The One Chance to be a Child (One Chance) report provided an evidence-informed data profile of the well-being of children and youth in Nova Scotia (NS). To promote the report, we engaged youth from across the province in a knowledge mobilization (KMb) project. The purpose of this research is to outline the methods of the project, as well as the priority areas identified by youth. 10 NS youth (grades 7–12) were recruited to take part in a three-phased KMb approach: (1) A sense-making workshop to learn and discuss the report, (2) The planning and delivery of a youth-led forum to engage decision-makers in dialogue around the report, and (3) A participatory data analysis workshop to identify priority areas from the report. Data were collected through audio-recordings, note-taking, and pictures of all materials. Five priority areas were identified by youth: (1) Access to Care– high-quality care in a timely manner, (2) Community Care– inclusive community solutions, (3) Open Minded Education– school curricula that reflects their needs, (4) Quality of Life and Basic Needs– living wages and healthy workplace policies, and (5) Youth Empowerment– youth voice embedded throughout all actions. Engaging youth around the findings of the One Chance report supported their voices being heard, and their well-being needs to be considered by decision-makers. Children and youth have a right to have their voices heard on issues affecting their well-being. The One Chance to be a Child (One Chance) report provided data on the well-being of children and youth in Nova Scotia, Canada. To promote the report, we engaged ten youth (grades 7–12) from across the province to be part of a Youth Leadership Team where they were invited to communicate the report to decision-makers and identify their main priorities from the report. The project was broken up into three phases. First, the youth engaged in a full-day workshop to learn about the One Chance report. Second, they planned, coordinated and implemented a youth-led forum to share information from the One Chance report to decision-makers. Third, they engaged in a participatory data analysis workshop to reflect on and prioritize the report findings based on their discussions in phases one and two. Five priority areas were identified and named by youth: (1) Access to Care, (2) Community Care, (3) Open Minded Education, (4) Quality of Life and Basic Needs, and (5) Youth Empowerment. Disseminating and prioritizing the One Chance report with youth supports having their voices heard, and their well-being needs considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".