Settler Colonial Structures of Domestication: British Home Children in Canada
Bibliographic record
Abstract
There has been a surge of research on Home Children in the past several decades, as the phenomenon previously unknown to many came into the spotlight. However, much of the historical research has focused on either the psychological and physical impacts on the children at the hands of their new “families” (there were many reports of child abuse and neglect) or the ways they were saved from their poverty in Britain by being sent to the colonies. This article will put this existing historical research into conversation with theories of settler colonialism, considering Home Children as a tool of domestication for the social reproduction of Canadian white settler society, which was paired with the forced removal of Indigenous peoples from their lands. This analysis stems from and is intertwined with personal reflections on my own family history as a white settler woman descending from a Home Child to explore the gendered labour of social reproduction as a crucial pillar in creating and maintaining settler colonial Canada. Following Lorenzo Veracini’s argument that settler colonialism is a distinct structure that uses domestication as one of its key tenets and relies on its “regenerative capacity”, this paper will explore how British Home Children were a key component of settler colonialism in Canada and how this history has manifested in the current gendered, racialized, and classed politics of “settling”.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.030 | 0.012 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".