Oh, How Sylvester Can Pester! And Other Poems More or Less About Manners by R. Kinerk
Bibliographic record
Abstract
Kinerk, Robert. Oh, How Sylvester Can Pester! And Other Poems More or Less About Manners. Illus. Drazen Kozjan. New York: Simon & Schuster, 2011. Print. “You be nice to me; I’ll be nice to you. / That agreement might work. It may get us quite far. / (And it could be what manners, in truth, really are.)” (1). Books filled with poems about manners must be relatively rare. If so, then a book filled with twenty rollicking, frank, vivaciously-illustrated poems about manners must be nearly unheard of. However, this is what Robert Kinerk and Drazen Kozjan have given us in Oh, How Sylvester Can Pester! Readers of all ages will enjoy Kinerk’s direct, extravagant rhymes. His approach is comprehensive: he provides poems on entry-level etiquette such as cleaning one’s room, saying “please” and “thank you,” and keeping one’s clothes on in public, while also exploring more complex courtesies, such as shaking hands with adults, being on time, and keeping quiet at the movies. Kozjan’s illustrations are rich in both colour and detail. His style has been widely described as “retro,” likely because his work shares a particular rosy-cheeked exuberance with the work of iconic predecessors such as Mary Blair. Kozjan’s is a style in which an entire story is contained within a few strands of hair or a precisely-arched eyebrow. Despite its rolling rhythms and cheeky illustrations, what is most winning about Oh, How Sylvester Can Pester! is its sophisticated approach to its topic. It even contains a poem about the fact that it’s bad manners to lecture others about their manners. “Manners aren’t lists of things you should do. / Manners help folks become easy with you,” Kinerk writes (12). It’s this deft touch that makes this book memorable and admirable. Oh, How Sylvester Can Pester! will be appreciated by primary-school readers (and their adults). The poems are best read out loud, but the illustrations should not be neglected. Highly recommended: 4 out of 4 starsReviewer: Sarah Polkinghorne Sarah is a Public Services Librarian at the University of Alberta. She enjoys all sorts of books.
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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 | 0.001 | 0.002 |
| 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 | 0.004 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.136 | 0.082 |
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".