Bibliographic record
Abstract
Sadler, Marilyn. Pass It On! Maplewood, NJ: Blue Apple Books, 2012. Print.Marilyn Sadler enjoys writing funny children’s stories and has authored over 30 books. Through her role as executive producer and writer for the Disney Channel, Sadler has seen some of her works turned into children’s movies and TV series. In Pass It On! Sadler puts a new spin on the traditional game of Telephone, with comical results.‘Cow is stuck in the fence! Pass it on!’ Cow’s friend, Bee starts the ball rolling, sending out a plea to the other animals, recruiting their help to rescue Cow. The original message quickly gets distorted and becomes increasingly absurd, leaving the reader wondering: will anyone come to Cow’s aid?With its simple plot and humorous characters, this story is fun, engaging, and perfect for shared reading with young children. Michael Slack, recognized for his humorous character art, shines in this illustrated work. He is skillful in his use of colour and texture, creating expressive depictions of the animals in the story while conveying a sense of urgency and excitement. The typeset used for the comic-book-like speech bubbles differentiates the characters’ speech from narrative aspects of the story and cues the reader to the tone and dynamic of the animals’ pronouncements.I recently read this to a group of four and five-year-olds, after playing the Telephone game with them. Throughout the story, the children responded with exclamations of, “That’s not right!” and a chorus of, “Pass it on!” as each animal communicated his or her misinterpretation of the message.Highly recommended: 4 out of 4 stars Reviewer: Maria TanMaria is a Public Services Librarian at the University of Alberta’s H. T. Coutts Education Library. She enjoys travelling and visiting unique and far-flung libraries. An avid foodie, Maria’s motto is, “There’s really no good reason to stop the flow of snacks”.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.491 | 0.425 |
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".