A multi-method study of youth development and wellbeing: a meta-narrative analysis and program evaluation study
Bibliographic record
Abstract
Youth are embedded within multiple environmental systems, developing within families, neighbourhoods, and multicultural communities. Such systems influence the formation of identity and wellbeing. It is important to monitor the wellbeing of youth across their environments, given the complexities of diverse youth experiences. Accordingly, the present dissertation comprises two studies to address the topic of youth development and wellbeing using multiple data collection techniques. In Study 1, a meta-narrative analysis was undertaken examining concepts of youth wellbeing across multidimensional indices. A search was performed across the grey literature base and seven indices fit the search criteria. Data were extracted using a codebook to guide a thematic analysis and critical appraisal to compare, contrast, and critique indices. Results showed three key findings. (1) Indices had some overlap to conceptualize wellbeing, using an average of six dimensions. (2) Data collection used similar levels of population-level statistics and self-reported data. (3) A large proportion of measures focused on youth deficits, with less focus placed on positive attributes. In Study 2, an evaluation was conducted assessing the impact of a school-based art program on the socio-emotional wellbeing of adolescents from three grade 8 classrooms, within one inner-city, multicultural neighbourhood. A mixed-method, multi-informant evaluation design was employed, and implementation processes of the program were assessed. Survey data and open-ended responses were collected from 74 students at three time-points (pre, post, follow-up), using multilevel modeling to examine time-points nested within students. Responses were also collected post-program from six artist facilitators and three teachers. Program implementation results showed high levels of fidelity, and high quality ratings. Results from multilevel models showed significant variation at the between-student level. Across students, significant improvements were found over time for art skill, self-expression, and confidence presenting. Qualitative data revealed themes across informants regarding the positive impact of the program on student growth. Findings also indicated the importance of a safe space for adolescents to learn about themselves, and be vulnerable. These two studies shed light on the multiple ways in which youth development and wellbeing are assessed, and the ways in which a local-level community program can support their wellness.
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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 | 0.101 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".