Bibliographic record
Abstract
Both an adventure-laced captivity tale and an impassioned denunciation of the marginalization of Indigenous culture in the face of European colonial expansion, Douglass Smith Huyghue’s Argimou (1847) is the first Canadian novel to describe the fall of eighteenth-century Fort Beauséjour and the expulsion of the Acadians. Its integration of the untamed New Brunswick landscape into the narrative, including a dramatic finale that takes place over the reversing falls in Saint John, intensifies a sense of the heroic proportions of the novel's protagonist, Argimou. Even if read as an escapist romance and captivity tale, Argimou captures for posterity a sense of the Tantramar mists, boundless forests, and majestic waters informing the topographical character of pre-Victorian New Brunswick. Its snapshot of the human suffering occasioned by the 1755 expulsion of the Acadians, and its appeal to Victorian readers to pay attention to the increasingly disenfranchised state of Indigenous peoples, make the novel a valuable contribution to early Canadian fiction. Situating the novel in its eighteenth-century historical and geographical context, the afterword to this new edition foregrounds the author's skilful adaptation of historical-fiction conventions popularized by Sir Walter Scott and additionally highlights his social concern for the fate of Indigenous cultures in nineteenth-century Maritime Canada.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.073 | 0.019 |
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".