Bibliographic record
Abstract
Thompson, Lauren. Polar Bear Morning. Illus. Stephen Savage. New York: Scholastic Press, 2013. Print.Ten years ago, Lauren Thompson and Stephen Savage collaborated on “Polar Bear Night”, which was a splendid picture book that swiftly became a New York Times best seller. “Polar Bear Morning” follows up on the simple story of a polar bear cub that ventures out onto the arctic tundra for an adventure, but this time our favourite cub meets a new friend. The story begins when the cub emerges from her dark den, peeks out at the clear blue sky, and follows the sound of seagulls. Soon after heading out into the snow and ice, she notices something tumbling down a snow hill. It’s a snow cub! The moment when the cubs first meet is beautifully portrayed in a two-page spread that shows two furry faces in profile looking at each other without words on the pages, which perfectly captures a child’s speechless, wide-eyed bliss upon meeting a new friend.The story continues with several charming scenes that show how the friendship develops: they climb the snow hill and tumble down together; they sprint beside the sea; they race past seals, walruses and whales; they pause at the ice’s edge; and finally, they jump into the sea together. It’s a delightful portrayal of a budding friendship, with simple, yet charming illustrations rendered in a gentle palette of soft blues, greys, pinks, and browns. This picture book is a joy to read and has all the makings of a beloved classic, including frolicsome illustrations, thoughtful design, and a captivating story. It’s a wholly satisfying picture book that will be a pleasure to read again and again.Recommendation: 4 stars out of 4Reviewer: Robert DesmaraisRobert Desmarais is Head of Special Collections at the University of Alberta and Managing Editor of The Deakin Review of Children’s Literature. A graduate of the University of Toronto’s Faculty of Information Studies, with a Book History and Print Culture designation, he also has university degrees in English literature and publishing. He has been collecting and enjoying children’s books for as long as he can remember.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.286 | 0.297 |
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".