Teaching about Missing and Murdered Indigenous Women, Girls, and 2SLGBTQQIA+ People: Implications for Canadian Educators
Bibliographic record
Abstract
The 2019 National Inquiry on Missing and Murdered Indigenous Women and Girls called on educators at all levels to raise awareness about the phenomenon of missing and murdered Indigenous women, girls, and 2SLGBTQQIA+ people (MMIWG2S) and its root causes as connected to centuries of colonial violence and ongoing systemic discrimination. This article responds to that call by showcasing the experiences of eight teachers already teaching about MMIWG2S, the recommendations of 11 adolescent Indigenous girl activists, and the guidance provided in the Their Voices Will Guide Us teaching and learning guide, published alongside the National Inquiry’s final report. We draw upon the combined perspectives to encourage teachers in Canada to address the issue of MMIWG2S with their students, moving past representations of colonial violence as historical to examining how it affects the lives and deaths of far too many Indigenous people in Canada today.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.066 | 0.034 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 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".