Bibliographic record
Abstract
Dear Readers,The number of books arriving on my desk every year is large, and it may be no great surprise to know that I see many attractively illustrated children’s books. I wish we could review them all, but alas the amount of space in our journal is limited. Ever since the publication of our first issue, I have been wondering what it would be like to be a child today with scores upon scores of beautifully designed and illustrated books available for enjoyment and acquisition at public libraries, bookstores, and online retailers. Of course, I had access to beautifully illustrated books when I was a child, just not nearly as many. It’s this bounty of riches in high quality book illustration that could signify that we are witnessing another golden age of children’s book illustration.Many scholars, critics, and avid readers will point to the late nineteenth and early twentieth centuries as the first “golden age” of children’s book illustration largely because this is when so many imaginative and attractive books were published, many of which are now regarded as classics. Delightful pictures alone do not make a book exceptional, they must complement an excellent story and innovative design. But as you read the reviews in this issue and future issues it may be worthwhile to notice how many times our reviewers comment upon the fresh and innovative illustrations, and then ask yourself if we are indeed witnessing a new golden age in children’s book illustration. Enjoy our new issue!Best wishes,Robert DesmaraisManaging Editor
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.033 | 0.008 |
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".