Portraits and Gravestones: Documenting the Transnational Lives of Nineteenth-Century British-Métis Students
Bibliographic record
Abstract
The educational histories of mid-nineteenth century British-Métis students illuminate the transnational travels of British-Métis students and their roles in reifying and challenging British-imperial norms about race, class, and gender in the British Empire. In this paper, photographic and object-based artifacts are interwoven with family correspondence and other archival documents to explore the complexity of British-Métis children’s life stories and the extensive connections between elite British-Métis fur-trade families to kith and kin in North America and Britain. Studio portraits of British-Métis children and their gravesites represent both the best and the worst outcomes of elite educations for British-Métis children and youth. The studio portraits represent the norms of British middle-class respectability that elite British-Métis students learned at colonial and metropolitan schools as part of the imperial project. Gravestones and burial sites, on the other hand, reflect the possibilities and realities of death and trauma that were intertwined with fur-trade children’s boarding school education. By traveling to and living in Britain, British-Metis children challenged metropolitan understandings of the place and role of Indigenous peoples in the Empire and left their marks in Britain in their lives and their deaths.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".