Amelia Paget’s <i>The People of the Plains</i>: Imperialist and Ethnocritical Nostalgia
Bibliographic record
Abstract
Twentieth-century representations of nostalgia as the mourning of a lost, idealized, organic communal identity often obscure the simultaneous but contradictory possibilities that nostalgia provides to narrative. Amelia Paget’s anthropological account of Cree, Ojibway, Assiniboine and Sioux First Nations in Western Canada, The People of the Plains, makes use of an “imperialist nostalgia” that praises the West’s bright future as part of the new nation, while at the same time it deploys this same colonial mourning to introduce another version of nostalgia that undermines any celebration of the liberal nation-state. In this 1909 text, then, Paget manipulates nostalgia’s capacity both to conceal and to articulate criticisms of the past, and the present, about which she writes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".