Expression of Story: Ethical considerations for participatory, community- and arts-based research relationships
Bibliographic record
Abstract
INTRODUCTION: This meta-research article considers the ethics and efficacy of a nonviolent, “braided” methodology used by a research study called “The Recognition Project.” The methodology of The Recognition Project interweaved participatory, community-, and arts- based approaches in an effort to create a cooperative, relationally oriented environment where three distinct communities of interest could contribute respectively—and collaboratively—to the sharing, creation, and public dance performance of stories about self-harm. The three communities of interest were university-based researchers, community-based researchers who had engaged in self-harm, and an artist team of choreographers, a musician, and professional youth dancers. Our article explores some of the experiences, as shared by dancers of the artist team, from narrative interviews following the final dance performance.METHOD: Data were collected through qualitative interviews conducted with six artist team members. A qualitative thematic analysis approach was used to identify the main themes.FINDINGS: What emerged was an overriding theme about Story and the power issues that came forward due to the personal and the collective aspects of Story. The power issues were related to individual and collective exercise of power, the use of dialogue to build a positive community, and the transformative potential for the artist collaborators to participate in such a study.CONCLUSION: While participatory, community- and arts-based projects are often taken up with the intention of facilitating research that will not harm, there are important and additional ethical considerations to be made in community-based collaborations that feature difference across perspective, experience, skill, and knowledge.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".