Deepening our understanding: Collaboration through online peer-to-peer participatory action research with children
Bibliographic record
Abstract
Child-led research is growing globally, yet there are still limitations for children's leadership in all phases of research. This article, co-written with adult and child researchers, examines child-led research undertaken online with 9 children from Ontario and Quebec over a one-year period. The article explores the process of participating in and collaborating on an online peer-to-peer participatory action research project from the brainstorming stage to recruitment, design, data collection, analysis, and dissemination of knowledge. While much literature exists on older children and youth leading research, this research provides a unique contribution to the literature on the possibilities of creating space for children ages 11 to 14 to lead research. This article finds that the child researchers most valued: (1) Play and fun; (2) Engaging in new experiences; and (3) Learning. The article concludes that child-led research is feasible, and it can create better research and provide a transformative opportunity for child and adult researchers.
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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 | 0.068 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.038 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".