Bibliographic record
Abstract
Pignat, Caroline. Poetree. Illustrated by François Thisdale, Red Deer Press, 2018. Caroline Pignat is a two-time Governor General Award winner and it’s easy to see why when one looks at her latest beautiful book. Each page of Poetree is simply delightful with short simple poems complemented by François Thisdale’s excellent illustrations. The illustrations perfectly invoke the feeling of the poem whether it be the frosty cold of a silent winter’s morning or the pure warm delight of a warm summer's day. The short length of the poetry and the everyday-vocabulary chosen by Pignat makes this book accessible to many readers, even those working on their English skills or who are new to poetry. For educators and librarians, this book would be an excellent addition to a program celebrating poetry. In fact, the style of the short poems and illustrations focusing on daily life could be showcased in the reading of this book and then learners could work on creating their own illustrated poems in the style of Poetree. The combination of eye-catching illustrations with high contrast text will no doubt delight audiences of all ages if used in story times and the overall simplicity of the language would allow newer readers to still engage, making this an excellent addition to classrooms and libraries. Recommended with Reservations: 3 stars out of 4 Reviewer: Lorisia MacLeod Lorisia MacLeod is an Instruction Librarian at NorQuest College Library and a proud member of the James Smith Cree Nation. When not working on indigenization or diversity in librarianship, Lorisia enjoys reading almost any variation of Sherlock Holmes, comics, or travelling.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.362 | 0.302 |
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".