Bibliographic record
Abstract
This essay analyzes the gendered ways in which settler states produce and manage their relationships to Indigenous women's deaths. I seek to complement Indigenous feminists’ critiques of the rhetoric of crime that predominates in conversations about murdered and missing Indigenous women, as well as Indigenous feminists’ analyses of the state's own masculinist violence. I argue the emotional–managerial performances by which contemporary settler states seek to exculpate and distance themselves from this violence repeat and intensify long histories of settler feminism. Rather than examining the figure of the murdered Indigenous woman, this essay interrogates her counterpart, the white settler woman who serves as a synecdoche for her country: modern, feeling, feminist, and most of all, just. I ground my analysis in a recent book of poetry by Rachel Zolf, Janey's Arcadia (2014), which uses experimental poetic techniques to re-present a nineteenth- and early twentieth-century textual archive that makes clear how actively and how zealously white women participated in the settlement of the Canadian prairies. In re-presenting historical texts through intentionally dissonant poetry, Zolf contests historical and contemporary constructions of Canada's benevolence in general, and of white settler women's innocence in particular. Zolf shows that articulations of settler women's empowerment serve to naturalize colonization, stripping it of its violence and framing settlement, and the state that carries it out, as beneficial to Indigenous people. I argue this book performs the rhetorically difficult task of describing the violence performed by white women in furtherance of Indigenous dispossession. Janey's Arcadia shows that cruelty toward Indigenous women is not the sole purview of individual male criminals who perform unthinkable acts. Instead, it demonstrates that the settler colonial project of eliminating Indigenous peoples can be performed in a distinctly feminine – and even feminist – register.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.026 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".