Bibliographic record
Abstract
Higgins, Ryan T. We Don’t Eat Our Classmates. Disney-Hyperion, 2018 This is a messy book. Ryan Higgins' drawings are much messier and less precise than his earlier books about Bruce, the bear. However, when you are Pamela Rex, a Tyrannosaurus rex starting school with a room full of delicious human classmates, things get messy, particularly when you have to spit them out. Ryan Higgins taps the absurd in both his images and text to keep children laughing. Penelope still wants to eat the children, even though her father “packed her a lunch of three hundred tuna sandwiches." There is also an image of Penelope trying to “make friends at recess,” but she is standing at the bottom of the playground slide with her mouth open. Penelope does eventually learn a small lesson in empathy when Walter, the class goldfish, bites her. Higgins draws Penelope as a stuffed toy Tyrannosaurus rex, perhaps to prevent children from being frightened. The children are represented by the usual politically correct collection of stereotypes, often identified by clothing. There is one Jewish (yarmulke), one Muslim (hijab), two black (tight curly hair), one Indigenous (braids), one Japanese (the only child with a shirt and tie), and several generic “brown” children. All of the children have dark hair. Blue-eyed blonds are conspicuous by their absence. In addition to being a fun book, this volume allows every child to claim the moral high ground. Every child can say, “I wouldn’t ever do that!”, because all children know that “we don’t eat our classmates.” While this is a book about being different, clashes of values, and learning to get along, it is mainly a book that will amuse children. Recommended for elementary school and public libraries. Recommended: 3 out of 4 stars Reviewer: Sandy Campbell Sandy is a Health Sciences Librarian at the University of Alberta, who has written hundreds of book reviews across many disciplines. Sandy thinks that sharing books with children is one of the greatest gifts anyone can give.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.252 | 0.188 |
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".