A Medieval New World: Nation-making in Early Canadian Literature, 1789-1870
Bibliographic record
Abstract
This thesis examines how medievalist narratives of nationhood developed in the early days of English Canadian literature, from 1789-1870. Early Canadian authors imagined a past for Canada tied not to the land but to cultural memory; they created a medieval history for Canada by adapting European medieval myth and legend. Adaptation was a powerful tool in the hands of authors struggling to negotiate North America's multiple colonial relationships: it allowed them to embrace European cultural histories, to stake a claim to those Old World cultural inheritances, while simultaneously appropriating those histories into new narratives for the New World. \nThis project, as the first large-scale study of medievalism in Canada, involved finding and cataloguing instances of medievalism in Canadian literature. The trends explored in this thesis are based on 443 works of Canadian medievalism published between 1789 and 1870.\nChapter One analyzes Canada's first literary magazines in the late eighteenth century. Responding to revolutions on both sides of the Atlantic, these magazines advocated a revolution not of arms but of manners, with medieval chivalric codes as the exemplar. Chapter Two turns to the literary aftermath of the Napoleonic Wars and the War of 1812. These wars instilled in many Canadian authors anxieties not only about France and the United States, but also about the role of empire in the modern world. In this new world order, medievalism became a source of validation, a keystone that held together a nation or empire's history from antiquity to the modern day. Chapter Three examines the reemergence of French-oriented medievalism after the failed rebellions of 1837-1838 and the ensuing unification of the Canadas. In the hands of English Canadian authors, even sympathetic French characters were stuck in the past, thus relegating their roles in Canada to those of cultural progenitors but not modern political participants. Chapter Four, on the period leading up to and immediately following Confederation, examines the expansion of racialized narratives of Canadianness to include pan-British and pan-northern conceptions of Canadianness. This northern identity particularly embraced Canada's history of Viking contact as integral to the nation's hardy northern character.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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 teacher head, 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".