Post-Pandemic Engagement of Youth in Virtual Environments: Reflections and Lessons Learned From the Development of a Youth Education Program
Bibliographic record
Abstract
The COVID-19 pandemic introduced new landscapes for research and public engagement participation. This shift was accompanied by significant challenges and unique opportunities for engaging youth as active participants and collaborators. This commentary will reflect on insights gained from conducting a variety of virtual youth engagement activities during the pandemic, within a rights-based and empirical approach. The team reflected on challenges, opportunities, and suggestions for engaging youth as participants and collaborators in research using virtual platforms. This commentary outlines opportunities for growth and challenges worthy of consideration for future virtual youth engagement activities. These considerations are put forth with the goal of upholding autonomy, diversity, and amplifying the voices of youth in research through virtual environments. Considering our insights on engaging youth, we hope to contribute to the expanding field of youth engagement, and advance future research that utilizes virtual modalities.
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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 | 0.024 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.005 | 0.012 |
| 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".