Participatory Hermeneutic Ethnography: A Methodological Framework for Health Ethics Research With Children
Bibliographic record
Abstract
When conducting ethics research with children in health care settings, studying children's experiences is essential, but so is the context in which these experiences happen and their meaning. Using Charles Taylor's hermeneutic philosophy, we developed a methodological framework for health ethics research with children that bridges key aspects of ethnography, participatory research, and hermeneutics. This qualitative framework has the potential to offer rich data and discussions related to children as well as family members and health care workers' moral experiences in specific health care settings, while examining the institutional norms, structures, and practices and how they interrelate with experiences. Through a participatory hermeneutic ethnographic study, important ethical issues can be highlighted and examined in light of social/local imaginaries and horizons of significance, to address some of the ethical concerns that can be present in a specific health care setting.
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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 | 0.189 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.011 | 0.046 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".