Reflexively Engaging in Studying Childhood Ethics and Agency: Implications for Conducting Participatory Research
Bibliographic record
Abstract
Researcher reflexivity in studying ethics and agency in participatory research with children is gaining recognition as a critical area of inquiry. Despite an appreciation of children’s voices, agency, right to participation, socio-emotional well-being, and welfare, our understanding of how these rights are upheld and enhanced in research remains understudied. Although under-explored, Arts-based participatory research shows promise in valuing children’s perspectives and well-being. This study focuses on how, as researchers, we can ethically engage with children's agency, balancing their development with safeguarding their socio-emotional well-being and respecting their cultural heritage and dignity. As an educator and reflexive researcher, I employed various reflexive tools such as jotting notes, field notes, and diary entries to investigate ethical challenges concerning children's agency in art-based participatory research. This inquiry was conducted in collaboration with the "Wellbeing" project within a temporary shelter for marginalized migrants, ‘Global Haven’ - a fictional name- in Montreal, Quebec. Over a period of two years, I wrote jottings and field notes based on a series of workshop events at Global Haven and as part of my involvement on the research team. In the thesis, I draw on and interpret these field notes, focusing on critical moments in the fieldwork. I conclude that researchers would do well to focus on ethics in research with refugees, especially refugee children. I suggest that working in the field as a reflexive observer is an excellent place to start. This study seeks to contribute to understanding how ethically engaging in research with children while reflexively valuing their agency, dignity, well-being, and cultural heritage
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.600 | 0.464 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.035 | 0.183 |
| Scholarly communication | 0.047 | 0.048 |
| Open science | 0.010 | 0.034 |
| Research integrity | 0.015 | 0.024 |
| Insufficient payload (model declined to judge) | 0.005 | 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".