Bibliographic record
Abstract
Introduction In the terrain that would eventually become the Dominion of Canada, it is not surprising that the literature of exploration was written almost entirely by men. By contrast, canonical narratives of settlement were largely penned by women. From an historical perspective, Central Canada’s settlement literature began with the texts that were written in the first half of the nineteenth century to entice emigrants from the British Isles to the New World. According to Carl F. Klinck, between 1815 and 1840 approximately 100 “travel and emigrant books about Upper Canada” appeared in Britain, of which he distinguishes William Dunlop’s Statistical Sketches of Upper Canada for the use of Emigrants (two editions in 1832 and a third in 1833) as “the most engaging of the lot.” Also popular was John Howison’s much-reprinted Sketches of Upper Canada (1821, 1822, 1825), which integrates advice for prospective emigrants with an account of his own travels and observations. Eyewitness testimonials were considered especially credible, such as T. W. Magrath’s Authentic Letters from Upper Canada (1833), a copy of which was owned by the Moodie family. The early 1830s saw the appearance of several important works of this nature, including the novels Lawrie Todd; or, The Settlers in the Woods (1830) and Bogle Corbet (1831) by Scottish writer John Galt, which reflect his experience in planning communities under the aegis of the Canada Company in the 1820s, and a tract by William Cattermole, whose recruiting lectures would soon entice John and Susanna Moodie to immigrate to Upper Canada. The generic nature of Cattermole’s Emigration .
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.020 | 0.029 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".