Bibliographic record
Abstract
Ten years, ten authors, ten critics. The Canadian Literature Centre/Centre de littérature canadienne reaches into its ten-year archive of Brown Bag Lunch readings to sample some of the most diverse and powerful voices in contemporary Canadian literature. This anthology offers readers samples from some of Canada’s most exciting writers of fiction, nonfiction, and poetry. Each selection is introduced by a brief essay, serving as a point of entry into the writer’s work. From the east coast of Newfoundland to Kitamaat territory on British Columbia’s central coast, there is a story for everyone, from everywhere. True to Canada’s multilingual and multicultural heritage, these ten writers come from diverse ethnicities and backgrounds, and work in multiple languages, including English, French, and Cree. Ying Chen | essay by Julie Rodgers Lynn Coady | essay by Maïté Snauwaert Michael Crummey | essay by Jennifer Bowering Delisle Caterina Edwards | essay by Joseph Pivato Marina Endicott | essay by Daniel Laforest Lawrence Hill | essay by Winfried Siemerling Alice Major | essay by Don Perkins Eden Robinson | essay by Kit Dobson Gregory Scofield | essay by Angela Van Essen Kim Thúy | essay by Pamela V. Sing
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.040 | 0.010 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".