The Urgency of Fostering Student Agency in Genocide Education
Bibliographic record
Abstract
While we teach with the assumptive belief that there is an inherent value in genocide education, there has been little discussion about what “good” genocide education looks like, let alone whether it is effective in diminishing the stereotypes, prejudice, and discriminatory behaviors that underlie genocidal policies and practices. This article argues that genocide education has the potential (albeit mostly untapped) to have a transformative influence on our students and the worlds in which they live. To tap that potential, though, involves us, as educators in genocide studies, recognizing the urgency of fostering student agency. We must practice genocide education in a way that nurtures and promotes a sense of agency in our students. To foster student agency through genocide education requires us to think about our classrooms not just as backward-looking portals to the past but as agentic spaces attuned to the urgent needs of the present and our future.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".