Create & Grow Strong: \nUsing Creative Exploration, Expression & Celebration to Foster Resilience in Youth
Bibliographic record
Abstract
This research explored the idea that a creative project undertaken in a group setting could help youth to cultivate the traits that contribute to increased resilience elsewhere in life. This thesis was revised based on findings derived from praxis, reflective practice and grounded theory research. Create & Grow Strong, a six-week workshop program and showcase celebration, was developed with art and play therapy in mind, but without the goal of direct psychotherapeutic intervention. There was strong evidence that this was successful in fostering feelings of pride, confidence and hopefulness and in creating an environment of trust that allowed for group discussion about issues prevalent in the local community. The study was based in Toronto’s Regent Park - an area associated with crime and poverty that was undergoing a government-initiated revitalization. This thesis considers the inspiration for the research, the existing work both by theorists and practitioners working in the fields of social work, education, psychology and interaction design. Also the author’s own design process, both technologically and, as the author built the workshops, the results and the insights gained from a grounded theory approach. Finally, potential future iterations of the work are discussed.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".