Bibliographic record
Abstract
Michaels, Anne. The Adventures of Miss Petitfour, illustrated by Emma Block. Tundra Books, 2015. The winner of numerous awards, Anne Michaels has earned her place among Canada’s most talented wordsmiths. Long a respected Canadian poet, her brilliant debut novel—Fugitive Pieces (1996)—brought her international acclaim. The Adventures of Miss Petitfour is Michaels’ first book for children. Emma Block is a young freelance illustrator who has already established a reputation for delicately feminine and delightfully quirky illustrations. Her work can be seen in children’s books, Hallmark products, and in tableware. This book represents a nearly perfect partnership between the author and the illustrator.Among other things, this is a book about the stories we like to tell and read. The books in the village bookshop near Miss Petitfour’s house are divided into two sections: ho-hum and hum. The former are books in which nothing ever happens, but are “full of interesting facts that would never come in useful” and the latter are adventure books.This charming little book is certainly not ho-hum, but neither does it offer grand adventures. The adventures of the unconventional Miss Petitfour and her sixteen fun-loving cats—all of whom go everywhere with her, quite literally wherever the wind takes them—are adventures of "just the right size—fitting into a single, magical day." These little adventures demonstrate that sometimes “the best things happen” when “things work out differently than you expect.”Young bookworms and aspiring writers will be delighted to find that Michaels offers them a peak behind the curtain, one that reveals some of the key elements in the construction of a story, and explains how these elements function with clarity and wit. For example, in the midst of a major digression in a story about a trip to buy marmalade, we are told that a digression is “when the story wanders off the point and gets lost” and that it can be the best part of a story. Several digressions follow naturally and are clearly marked as such. In another story, we are told that a coincidence “is something that happens at just the right moment,” and that stories use them “to fix up tricky tangles”, following which, coincidentally, the story—about a confetti factory explosion—cleverly and humorously demonstrates the technique several times in rapid succession.The name of the main character—Miss Petitfour—is somewhat unexpected, but the delicate and ornate nature of the French pastry known as a petitfour makes it a suitable metaphor at the heart of a little book that celebrates little everyday adventures, decorative language, and fanciful illustrations in a way that is light and sweet and fun. This book is very highly recommended for children of all ages and is well suited for reading aloud.Highly recommended: four stars out of fourReviewer: Linda QuirkLinda taught courses in Canadian Literature, Women's Writing, and Children's Literature at Queen's University (Kingston) and at Seneca College (Toronto) before moving to Edmonton to become a teaching librarian at University of Alberta’s Bruce Peel Special Collections. Her favourite children's book to teach is Hana's Suitcase, not only because Hana's story is so compelling, but because the format of this non-fiction book teaches students of all ages about historical investigation and reveals that it is possible to recover the stories of those who have long been forgotten by history.
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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 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.077 | 0.029 |
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".