Bibliographic record
Abstract
Liwska, Renata. Red Wagon. New York: Philomel Books, 2011. Print. This picture book is designed to be read by an adult to young children. Somewhat reminiscent of Peter Rabbit stories, the characters in this book are woodland animals. The plot is simple. Lucy is a young fox who has just got a red wagon. She wants to play with it, but her mother sends her to the market for vegetables, so on the way, she imagines great adventures. Lucy’s companions on the journey are a bear, a rabbit, a hedgehog and a raccoon. Liwska’s illustrations are endearing. The illustrations are two-page spreads with the animals in various imaginary and “real” places. With each new imaginary scene, the red wagon morphs into something different. First it is a boat on the high seas, then a covered wagon, then a gypsy caravan at the market, then a train car, a space ship, and a piece of construction equipment. In each scene the animals have props or clothing to match the theme. In the space ship scene, the raccoon acquires a third eye to look alien. All of the illustrations are done with fine pencil strokes that make the animals look like cuddly stuffed toys. Strangely, the text is generic and could be divorced from this work and applied to a completely different set of illustrations. There is no mention of Lucy being a fox and no references to her companions or the wild changes in scenery. For example, the text that accompanies the elaborate covered wagon scene, in which the animals have cowboy hats and bandanas and Lucy has a boots and a sheriff’s badge reads: “Soon the rain stopped and the sun came out. She continued on her way.” Lucy could have been an elephant, a robot, a child or an ant, as long as she had a red wagon. While this will make no difference to a young child’s enjoyment of the book, the text could have been so much more engaging if the animals had been given names and the text reflected the content of the illustration, or for example, “Rabbit pushed, while Lucy pulled.” Similarly, the European look and feel of the book will make it more difficult for Canadian children to identify with the story. There are no wild hedgehogs in Canada and most Canadian children do not go to a market for vegetables – they go to a supermarket. Even if they did go to a farmers’ market they would not find tents with flags, gypsy caravans, stilt walkers, jugglers and trapeze artists. However, oddities aside, this is a book that pre-readers and new readers will love. Recommended: 3 out of 4 starsReviewer: Sandy CampbellSandy is a Health Sciences Librarian at the University of Alberta, who has written hundreds of book reviews across many disciplines. Sandy thinks that sharing books with children is one of the greatest gifts anyone can give.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.298 | 0.349 |
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".