Marginalized Urban Indigenous Youth and the Virtual World of Second Life: Understanding the Past and Building a Hopeful Future
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A small independent high school in the Canadian West is using the affordances of the virtual world of Second Life to explore and reconstruct the colonial past of their students: marginalized urban Indigenous youth. The affordances of the virtual world make it possible to reconstruct the past, deconstruct the present and create a possible hope-filled future. This process is underpinned by pedagogies of engagement and emancipation on three virtual islands (sims) in the virtual world. The past was reconstructed and can be deconstructed on the Negan Tapeh sim. Negan Tapeh is a Cree phrase meaning “look to the future.” When the activities and quests associated with exploring and understanding the events of the past and their impact on the present are complete, participants are transported to the virtual present on the Boyle Street sim.Boyle Street is an inner-city area in Edmonton, Alberta, where most of the youth live or gravitate to. In Canada and the United States, inner city areas have historically been synonymous with depressed and run-down parts of the city where petty crime, violence and substance abuse are woven into the fabric of daily life. On Boyle Street, the youth are tasked with completing assignments (quests or hunts) distributed by teachers (scripted agents) in the sim’s Boyle Street High School. When the three quests are completed, participants receive their key to the future. The future unfolds on the third sim Urban Hope.This paper underlines the importance of the virtual world in educational projects with marginalized youth.
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.
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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it