Learning about the Lifeworlds of Trans, Non-Binary and Gender Non-conforming Children through an interactive video game
Bibliographic record
Abstract
This workshop will explore the value of video game technology in educational settings for supporting and including transgender students. The Gender Vectors project is comprised of a team of researchers from Simon Fraser University, working with transgender, non binary, and gender nonconforming (T/NB/GNC) children and youth in the Lower Mainland (B.C.) to produce a video game as an educational tool. Since 2015 our team has been working to build a prototype of an interactive gaming resource that makes visible the experiences of precarity and vulnerability, as well as resilience, of T/NB/GNC children and youth. The game will also function as database for available resources for T/NB/GNC children and youth in the Greater Vancouver Area, and simultaneously make visible what resources and forms of support- social, educational, medical, and cultural- are still lacking. Through our workshop, we will invite attendees to test the prototype of our game, and engage in a discussion of how to create inclusive educational environments for T/NB/GNC children and youth.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".