Enabling youth participation in school-based computer-supported community development in Canada
Bibliographic record
Abstract
Schools are a main setting for health promotion for youth. A qualitative case study was undertaken in an inner-city, Canadian school. It explored factors that enabled and constrained youth in the process of a school-based computer-supported community development (CD) project. Nineteen grade seven and eight students worked with four adult facilitators for 12 weeks. They completed a community assessment, planned and implemented actions to improve their school environment. Data were collected by: youth and adult interviews, participant observation, content analysis of online postings and two surveys. Constant comparison and triangulation from various data sources and methods were used to verify themes. Themes were categorized as intrinsic or extrinsic enabling and constraining factors. Intrinsic enabling factors were youth' s perceptions that they were making a difference, and feeling recognized for and having ownership of their work. Extrinsic enabling factors included flexibility in youth's choice of activities, supportive adults and community members and the use of incentives. Intrinsic constraining factors were the perceived slow pace of the CD process, and difficulties in getting group consensus/decision-making. Extrinsic constraining factors included: school disruptions and schedules, a lack of 'buy-in' from teachers and parents, and resource demands-people and computers. Relationships between these factors are noted. Research and practice implications regarding school-based CD to promote youth resiliency 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 | 0.001 | 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 | 0.011 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".