Bibliographic record
Abstract
Navarro-Powell, Luciana. My Dad is the Best Playground. Mississauga: Random House of Canada Limited, 2011. Print. Originially from Brazil, Luciana Navarro Powell moved to the U.S. in 2002. Navarro-Powell has worked as a professional illustrator for approximately 14 years. Her current media of choice is the digital brush, which she used to illustrate My Dad is the Best Playground. My Dad is the Best Playground is a board book that is delightful and easy to read to toddlers. From the moment Dad arrives home, the story describes all of the ways in which he can be used like a playground and how the children in the story interact with their father, from climbing on him to being twirled about by him. Each of the actions cleverly relates to actions that the children would also be able to do at a real playground. The truly wonderful part of the story is the illustrations. For pictures that are simple, they convey so much motion and interaction. The colour palette used is pleasing to the eye. The true test of any book is the reaction of the target audience. The toddlers daycare class to whom I read the story could easily identify the boy and girl and other household items in the pictures. They also thought it was funny to see the children interact with their father in different ways. This was a lovely story to read to toddlers and illustrated the positive interactions Dads have with their children. Recommended: 3 out of 4 Reviewer: Virginia PowVirginia is the Maps Librarian for the William Wonders Map Library and a Public Services Librarian for the Cameron Science and Technology Library at the University of Alberta. In her free time she enjoys hiking, camping, running, cross country skiing or anything in the outdoors with her favorite partners in crime; daughter, husband and very large mutt.
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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 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.318 | 0.233 |
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".