Virtual Reality and Youth Incarceration: Methodological Reflections from a Media Education and Research Program
Bibliographic record
Abstract
Background: This research aimed to provide young people in a juvenile rehabilitation centre (JRC) with access and exposure to virtual reality (VR) as a growing media technology industry, to offer media education that was fun and engaging, and to introduce the digital arts to participants as a potential career path. The project evolved through a partnership with the Washington State Librarian who, as a part of her role overseeing public library activities, wanted to ensure that newly acquired VR equipment was made available to as many people as possible. This effort included libraries within sites of incarceration. Analysis: This article presents a reflective and analytical discussion on the success and challenges of creating, implementing, and researching a VR art design program in a JRC. Conclusions and Implications: Carceral logics are entangled in research and education, in constant tension with anti-oppressive methods in place. Improvisational action as a design method in media education programs, including VR art design with incarcerated youth, may support greater participation and stronger research outcomes.
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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 | 0.068 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.030 | 0.034 |
| Scholarly communication | 0.020 | 0.009 |
| Open science | 0.005 | 0.019 |
| Research integrity | 0.004 | 0.009 |
| 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".