White Civility: The Literary Project of English Canada
Bibliographic record
Abstract
"In White Civility Daniel Coleman breaks the long silence in Canadian literary and cultural studies surrounding Canadian whiteness and examines its roots as a literary project of early colonials and nation builders. He argues that a specific form of whiteness emerged in Canada that was heavily influenced by Britishness. Examining four allegorical figures that recur in a wide range of Canadian writings between 1820 and 1950 - the Loyalist fratricide, the enterprising Scottish orphan, the muscular Christian, and the maturing colonial son - Coleman outlines a geography of whiteness that remains powerfully influential in Canadian thinking to this day." "Blending traditional literary analysis with the approaches of cultural studies and critical race theory, White Civility examines canonical literary text, popular journalism, and mass market bestsellers to trace widespread ideas about Canadian citizenship during the optimistic nation-building years as well as during the years of disillusionment that followed the First World War and the Great Depression. Tracing the consistent project of white civility in Canadian letters, Coleman calls for resistance to this project by transforming whiteness into wry civility, unearthing rather than disavowing the history of racism in Canadian literary culture."--BOOK JACKET.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.038 | 0.013 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".