Bibliographic record
Abstract
Schiller, Abbie. A Little Book About Feelings. California: The Mother Company, 2013. Print.A Little Book About Feelings is a product of Ruby’s Studio, a video and print series designed to educate children and parents with respect to social and emotional learning. Adapted from the video “Ruby’s Studio: The Feelings Show,” the purpose of this book is to educate children on how to understand and communicate their feelings. The Ruby Studio is produced by The Mother Company, which is a mom-run American-based company dedicated to providing resources for parents who seek to offer their children educational entertainment.With simple text and beautiful stills of handcrafted caricatures from the program as illustrations, this book is most useful for younger children. It begins by explaining what feelings are, then describes how some feelings may feel, as well as how feelings change. The story also deals with the importance of expressing your feelings as well as listening to them.Overall, this book is a helpful resource for children and parents. With bright illustrations and simple text, this book serves as an informative and entertaining resource on feelings for children.Highly recommended: 4 out of 4 stars.Reviewer: Robin DesmeulesRobin is an Academic Librarian Intern at the J.W. Scott Health Sciences Library at the University of Alberta. Robin is an avid devourer of fiction of all kinds.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.086 | 0.057 |
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".