Bibliographic record
Abstract
At the beginning of the twenty-first century, poetry in Canada-writing and publishing it, reading and thinking about it-finds itself in a strangely conflicted place.We have many strong poets continuing to produce exciting new work, and there is still a small audience for poetry; but increasingly, poetry is becoming a vulnerable art, for reasons that don't need to be rehearsed.But there are things to be done: we need more real engagement with our poets.There needs to be more access to their work in more venues-in classrooms, in the public arena, in the media-and there needs to be more, and more different kinds of publications, that make the wide range of our contemporary poetry more widely available.The hope that animates this new series from Wilfrid Laurier University Press is that these volumes will help to create and sustain the larger readership that contemporary Canadian poetry so richly deserves.Like our fiction writers, our poets are much celebrated abroad; they should just as properly be better known at home.Our idea has been to ask a critic (sometimes herself a poet) to select thirtyfive poems from across a poet's career; write an engaging, accessible introduction; and have the poet write an afterword.In this way, we think that the usual practice of teaching
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.579 | 0.512 |
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".