Bibliographic record
Abstract
Hutchins, Hazel. Cat Comes Too. Illus. Gosia Mosz. Toronto: Annick Press, 2013._____________ Dog Comes Too. Toronto: Annick Press, 2013.Nicely sized for children’s hands, these two little board books should delight both pre-schoolers and beginning readers. Their story lines are simple and humorous.In the first, a curious kitten follows a pair of human feet (the entire body is never revealed but seems feminine) up the stairs to the attic and, there, has a fine frolic amidst the storage. In the second, a puppy follows a heavy-booted pair of legs (gender unclear) on an outdoor hike that proves challenging, but not impossible, for the small canine striver.Gosia Mosz’s colorful line drawings give us, simultaneously, both the world view of each young pet and a sense of its indomitable personality. With very few words, and a vocabulary level well within the range of most three- to six-year-olds, Hazel Hutchins produces a delightful amount of word play, particularly in Dog Comes Too: “Too far Too hot Too tired, pup? Big rest Two friends To the top Together” (Dog…pp.15-19)(For the children who read this book, a formal lesson on homonyms may come years later, if at all; no matter. They will have internalized the concept, anyway.)In these works, Hutchins and Mosz demonstrate the features of good composition for the very young: simple plotlines; recognizable settings; text that is readily memorized, then read; illustrations that are wedded to the text; characters that are lovable; and a viewpoint not unlike their own--all this and witty wording, too. Brilliant.Highly Recommended: 4 out of 4 starsReviewer: Leslie AitkenLeslie Aitken’s long career in librarianship involved selection of children’s literature for school, public, special, and university collections. She is a former Curriculum Librarian at the University of Alberta.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.324 | 0.202 |
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".