“Fugitive Visions”: Cultural Pseudomemory and the Death of the Indigenous Child in the Indian Poems of Duncan Campbell Scott
Bibliographic record
Abstract
Whether describing a fictional child’s decease in the Canadian wilds or the painfully real death rates in Indian Residential Schools, poetry and policy entangle in Duncan Campbell Scott’s depictions of Indigenous child mortality. The Confederation Group poet-bureaucrat is perhaps most infamous for his architectural role in the IRS system: it was his 1920 amendment to the Indian Act that legislated mandatory attendance at the chronically underfunded and inherently violent institutions. Yet the relationship between Scott’s responses to consistent reports documenting horrific rates of death and disease in IRS and his insistence that Canadian poets were the stewards of cultural memory for the young colonial nation has largely escaped critique. This paper makes this relationship visible by investigating how Scott’s characterization of Indigenous child mortality participates in the network of “administrative fictions” that governed IRS policy during and beyond Scott’s tenure. Scott’s depictions of dead, dying, and neglected Indigenous children reveal a fiction of neglect that undermines divisions between his so-called “Indian poems” and early-twentieth-century Aboriginal Affairs policy. This fiction implicitly undermines critiques of the IRS system by constructing an historically distant narrative in which the Indigenous child is always already subjected to the physical violence of residential schools within his/her own community. It fabricates a cultural pseudo memory for Anglo audiences in which poetry functions as an administrative technology — a masked violence reverberating at the literary substratum of the bureaucratic fictions which continue to obscure and forestall justice for Indigenous families and communities in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".