The influence of Survivor stories and a virtual reality representation of a residential school on reconciliation in Canada
Bibliographic record
Abstract
Indigenous Peoples in Canada have endured many genocidal efforts, such as residential schools. Across the country, initiatives to promote critical historical education about residential schools are underway, ranging in duration, content, and immersion. In this study, we tested whether a promising high-immersion approach, a virtual reality residential school, could improve non-Indigenous participants' attitudes and feelings toward Indigenous people. We compared the effects of the virtual residential school to a transcript condition, in which participants read the transcripts of the narration that accompanied the virtual residential school, and an empty control condition. The study had three time points: Baseline ( N = 241), intervention ( N = 241), and follow-up ( N = 132). Immediately following the intervention, what participants learned about the residential school, both through virtual reality and reading the transcripts, increased non-Indigenous participants' empathy, political solidarity, and outgroup warmth for Indigenous people, relative to the control. The virtual reality school, but not transcripts, also increased privity relative to the control. These effects decreased over time. In summary, though both written and virtual reality forms of critical historical education were effective in the short term, to maintain the long-term effects of critical historical education, ongoing or recurring education is likely necessary. These results extend the virtual reality literature to unstudied concepts (political solidarity, privity) and critical historical education literature to a new form of media (virtual reality). We discuss the findings in relation to literature on critical historical education and virtual reality as well as outline future directions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".