Bibliographic record
Abstract
A brilliant sun streams through the room's tall windows.I am at an event hosted by First Nations House at the University of Toronto.It is the early 2000s.We are upwards of ffteen people gathered in a circle, at ease, yet riveted by the conversation.Te speaker is mixed-race nehiyaw iskwew (Cree woman) scholar-activist, author, and artist Robyn Bourgeois and the topic colonial constructions of Indigenous women as disposable.It is my introduction to the issue of missing and murdered Indigenous women, girls, and two-spirit people (MMIWG2S) across what many now call Canada.Bourgeois' stark, impassioned critique provoked my anger and activist impulses, which are, not incidentally, among the white settler reactions to Indigenous struggles that I scrutinize in this book.Not long after, I became a non-Indigenous member of No More Silence (NMS), a group of Indigenous women and non-Indigenous women dedicated to raising awareness about the issue.I have stayed connected ever since.In the intervening years, public awareness of MMIWG2S people has increased exponentially, thanks to decades of organizing by Indigenous "warrior women" (Bourgeois 2014), so much so that the Trudeau government fnally launched a public inquiry into the matter in 2015.At the time, however, the topic rarely made it onto the public radar and was certainly new to me.Tat talk at First Nations House became a defning moment of my next decade, ultimately propelling me to research what I call the solidarity encounter between Indigenous women and white women in a contemporary Canadian context.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.579 | 0.378 |
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".