Engagement, Authenticity, and Advocacy in “Youth Uncensored”: Ethics in Applied Theater Research With Street-Involved Youth
Bibliographic record
Abstract
“Youth Uncensored” was an applied theater project with youth affiliated with an arts-based, nonprofit organization serving street-involved youth. The organization identified the need to educate service providers about the youth’s experiences to better meet youth’s needs. The youth were involved in all aspects of the process of creating workshops for service providers, from generating content for our scenes to devising, rehearsing, and performing scenes for service provider audiences, and participating in forum theater activations, in talk-back sessions, and in evaluating the project. For an evaluation of outcomes for youth, the youth created a 30-min video exploring the projects’ benefits and challenges. Through a close reading of the video, this article addresses the ethical issues that arose in relation to engagement, authenticity, and advocacy. Our ongoing efforts at negotiating this ethical terrain were crucial for the endurance and efficacy of the project.
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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 | 0.097 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.051 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".