Finding a Voice
Bibliographic record
Abstract
This article uses a Positive Youth Development framework to explore the experiences of six experiential youth coresearchers (YCs) in the Youth Injection Prevention (YIP) participatory research project, and the parallel track process of empowerment and capacity building that developed. The YIP project was conducted in Metro Vancouver at the BC Centre for Disease Control and community organizations serving street-involved youth. A process evaluation was conducted to explore themes in the YCs experience in the project, as well as process strengths and challenges. Semistructured interviews with the YCs, researcher field notes, and team meeting and debrief session minutes were analyzed. The YIP project appears to have exerted a positive influence on the YCs. Positive self-identities, sense of purpose, reconceptualization of intellectual ability, new knowledge and skills, supportive relationships, finding a voice, and social and self-awareness were among the positive impacts. Process strengths included team-building activities, team check-in and checkout sessions, and professional networking opportunities. Process challenges included the time required to help YCs overcome personal barriers to participation. The YIP project demonstrates that participatory research with street-involved youth is a viable research option that contributes to positive youth development and empowerment.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.053 | 0.019 |
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".