Governing Disappearance: Re-figuring Canadian Responses to Violence Against Indigenous Women and Girls
Bibliographic record
Abstract
This dissertation considers the history of Canadian policy responses to violence against Indigenous women and girls. I think through how these policy responses constitute processes that figure Indigenous women as objects of policy cut off from social relations and histories. In turn, these measures erase Indigenous agency and augment structures that sustain the disappearance of Indigenous women and girls. In this way, I expose how knowledge production is implicated within processes of disappearance and how relations of elimination are reproduced within policy responses to violence. I argue that settler-expert discourses subtly reassert state power through narratives of care by figuring Indigenous women and girls as damaged.\nI build upon Eve Tucks (2009) writing on deficit models of advocacy and Michel Foucault (1978) and Wendy Browns (1995) analysis of knowledge production to interrogate the assumptions emerging from expert discourses and truth-telling commissions. My work also draws on critical insights from 15 key informant interviews to consider specific policies within four areas: social planning, harm reduction, human rights, and policing. With these theoretical and methodological insights, I undertake a discourse analysis to consider the figuration of Indigenous women across 17 government and nongovernmental reports from the 1960s to the early 2000s.\nI examine the creation of policy figures as a technique of governing. Through this work, I consider how expert discourses produce new policy figures and generated new techniques of regulation and surveillance that targeted Indigenous women and expanded outward to target Canadian society. My work finds that the downloading and privatization of public and social responsibility to the community and the individual persisted across the postwar period and were enduring facets of disappearance. Expert discourses of care were central in depoliticizing the assertions of Indigenous peoples and their allies while normalizing state power.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.062 | 0.041 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".