Everyday Ethics: Framing youth participation in organizational practice
Bibliographic record
Abstract
Much of the literature on ethical issues in child and youth participation has drawn on the episodic experiences of participatory research efforts in which young people’s input has been sought, transcribed and represented. This literature focuses in particular on the power dynamics and ethical dilemmas embedded in time-bound adult/child and outsider/insider relationships. While we agree that these issues are crucial and in need of further examination, it is equally important to examine the ethical issues embedded within the “everyday” practices of the organizations in and through which young people’s participation in community research and development often occurs (e.g., community-based organizations, schools and municipal agencies). Drawing on experience from three summers of work in promoting youth participation in adult-led organizations of varying purpose, scale and structure, a framework is postulated that presents participation as a spatial practice shaped by five overlapping dimensions. The framework is offered as a point of discussion and a potential tool for analysis in examining ethical issues for young people’s participation in relation to organizational practice.
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 | 0.026 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.014 | 0.070 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.005 |
| 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".