Bibliographic record
Abstract
Hughes, Susan. Bath Time. Annick Press, 2017.Hughes, Susan. Play Time. Annick Press, 2017.Hughes, Susan. Nap Time. Annick Press, 2017. This is a set of board books on the activities of daily living: sleeping, bathing, and leisure. The concepts are introduced using high resolution stock images of animals paired with words related to the pictures.The “Bath Time” book illustrates the differences and similarities between humans and animals interacting with water. Actions like soaking and splashing are shown, and activities unique to animals like fluttering and licking are depicted. The “Play Time” book shows animals interacting in different environments: trees, snow, water, ice and grass. It also shows animals playing alone and together. The play-words used in this book can be applied to human interaction. The “Nap Time” book’s images show animals sleeping and yawning much like humans would, and shows the natural ways animals sleep that are different from humans (upside down, or in a tree). This book introduces synonymous words for napping like dozing and snoozing, and associative words like snuggling and cuddling.Each book concludes with the question “How do you nap/play/bathe?” which opens up opportunities to talk about these activities, learn word association, and learn about differences between animals and humans. These books bring a new perspective to these activities through the use of animal photos and would be appropriate for prekindergarten children. I would recommend them for public libraries.Highly recommended: 4 out of 4 starsReviewer: Tabatha Plesuk Tabatha Plesuk, is a first year MLIS Student at the University of Alberta (who spends free time teaching dance to children ages three to fourteen) with an enthusiasm for children’s books.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.235 | 0.211 |
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".