Bibliographic record
Abstract
While poetry would eventually enable Québécois literature, and subsequently Acadian, Franco-Ontarian, and Franco-Manitoban writing, to make the transition to modernity, it had first to pass through a long period of uncertainty and obscurity. Even in 1981, Laurent Mailhot and Pierre Nepveu maintained that up until the end of the nineteenth century, “les rimeurs franais d’Amérique imitent, racontent, prêchent, se plaignent, décrivent, chantent mais n’ écrivent guère.” Nonetheless, the sheer bulk of the Textes poétiques du Canada français ( TPCF ) remains striking: twelve volumes covering the period from 1606 to 1867 (10,000 pages, 3,857 poems, 227,175 lines), published between 1987 and 2000. Furthermore, the prefaces accompanying the poetry identify and define the development of two and a half centuries of a literary life which had, so far, never been considered as autonomous, but rather as a tributary of other historical, political, and social domains. Who would have thought that French Canada produced so many poems? While the TPCF may not represent a fundamental shift of the milestones in the history of French-Canadian poetry that have been established over the course of several centuries, the collection is a vitally important achievement. Functioning within both synchronic and diachronic perspectives, it uncovers, classifies, and puts into context thousands of compositions in verse.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.123 | 0.042 |
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".