Bibliographic record
Abstract
Stutson, Caroline. Cats’ Night Out. Jon Klassen. Illus. Toronto: Simon & Schuster, 2010. Print. This is an immediately appealing and well designed book – a pleasing convergence of balanced palettes and retro details. Sophisticated and stylish little urban cats cavort throught an overview of twentieth century dance styles against the backdrop of an understatedly cool Gotham night. The minimal text is mindfully integrated into the page design and its counting rhyme cadence comes to an enjoyable visually unstructured, cartoonish climax. When I read Cats’… to myself I was concerned that it shared one short coming with other attractive children’s books. Did the level of textual comprehension required, complexity of the popular culture references and the dark, low contrast palette cohere into a narrative and visual text that is holistically appropriate for a particular children’s age group? It’s discouraging when artful and ambitious books elude toddlers and preschool age audiences while seeming too simplistic to older children to offer sufficient engagement. Such books wash over children leaving them unmoved. Creating a beautiful picture book - which Cats’ Night Out certainly is - is a great accomplishment. Creating a picture book that is beautiful and that is truly directed at and calibrated for children is even more challenging. I knew that Cats’ Night Out would please discerning adults but, what little sartorialist cat-lover and junior aficionado of dance and monochromatic retro architecture would have an affinity for this book? Well, as it turns out, my four year old loves it and goes back through the book to examine all the details and explain which shoes, clothes and colours are the best and ask me baffling questions about “polka dotted Swiss” (I had to look it up – it’s a vintage fabric style). Very well done, indeed. Recommended: 3 out of 4 stars Reviewer: Matilda RocheMatilda spends her days lavishing attention on the University of Alberta’s metadata but children’s illustrated books, literature for young adults and graphic novels also make her heart sing. Her reviews benefit from the critical influence of a four year old daughter and a one year old son – both geniuses. Matilda’s super power is the ability to read comic books aloud.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.251 | 0.190 |
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".