Killing the Indian in the Child: Materialities of Death and Political Formations of Life in the Canadian Indian Residential School System
Bibliographic record
Abstract
Drawing on archival materials, including legislation and policy under the Indian Act (1876), and contemporary accounts circulated in the Canadian news media, this dissertation brings together theories of biopolitics and psychoanalytic accounts of the death drive to explore strategies of subject-formation and self-making within the circuitry of the Canadian Indian Residential School System (IRS), 1883-1996. The dissertation excavates some of the IRS founding mythologies, the logics subtending it, and elaborates some of its effects. Provoked by the IRS quo animo, “Kill the Indian in the Child,” the dissertation asks: 1) By what logics did “killing the Indian in the child” register in the colonial commonsense? In other words, how did this paradoxical warrant to simultaneously sacrifice and save (sacrifice to save) make sense? 2) Within the IRS, how was this figurative itinerary literalized on actual child bodies? By what means, and along which axes, was “the Indian” sliced from “the child,” and the former exposed to death and the latter subjected to technes of saving? 4) What kinds of politics did this paradoxical warrant of simultaneous death and saving inaugurate, produce, formalize? Examining the promise and limitations of archives, the dissertation resists recuperative action towards the redemption of subjects and subjectivities as lost but knowable objects. Instead, I point to events, subjectivities, moments, and bodies that seem to ‘slip’ or ‘overflow’ the archive, that direct us to indeterminate spaces of partial presence. In so doing I pursue a form of performative encounter with that which importantly remains unfixed. Each chapter frames its own form of writing into disappearance, and is less concerned with ratifying the veracity of a particular account than in understanding the terms that structure its non-recoverability through and against the archival drive to fix and claim. Considering the untimely quality of IRS violence, I consider the disappearance of the Indigenous child body as a sign whose tenuous evidentiary status connects questions of sexuality and colonial worlding with the logistical workings out of the fantasy of eradication through the mundane operations of everyday life.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.049 | 0.057 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".