Bibliographic record
Abstract
After GenocideRefugee Lifeworlds was on the syllabus for October 24, 2023.I had listed the keywords and concepts for that graduate seminar at the University of British Columbia's Institute for Gender, Race, Sexuality, and Social Justice as debility, refugee studies, and southern disability studies.Somehow I had bypassed genocide, but my students refused to mirror this elision, remarking on the "triggering" nature of the text, given the televisual experience of the mass murder and impairment of Palestinians in Gaza with which our myriad and various screens were currently inundated.They couldn't read the book; they wouldn't read the book; at some point, the two became the same refusal.I let it go; I let them go.I, too, struggled to process the implications of Y -Dang's story about the 4 million Cambodians who survived the genocide, only recently recognized as such in 2018.I thought about the temporal lag between the event of genocide and the recognition of the event of it; that perhaps the insistence of this lag is by design, built into the frameworks that govern genocide's epistemic and juridical recognition: genocide cannot be perceived as it is happening.Y -Dang reminds us that to "speak of the genocide as an event separate from the calculations of empire that came before and after it enables an eclipsing of the longue durée of imperial violence" (xi).We, as scholars and witnesses to the unfolding violence, were immersed in debates between so-called genocide experts about whether-by way of the extent, the intent, the scale, the quality, the quantity, all being the very metrics on which such adjudications rest-Israel was genociding Gaza.The United Nations' 1948 international genocide conventionitself an artifact of numerous genocides and forged by imperial and settler-colonial powers that selectively respond to some genocides
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.175 | 0.058 |
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".