Bibliographic record
Abstract
Love, Jessica. Julian is a Mermaid. Candlewick Press, 2018. Jessica Love’s first book, Julian is a Mermaid, lives up to her last name: it is a book about love. Julian, a young boy, dreams of being a mermaid. He and his abuela (Spanish for grandmother) go swimming every weekend and on the way home, Julian watches women in their mermaid dresses on the subway. He dreams of becoming a mermaid too, and in the end (spoiler), although he worries about his abuela’s reaction to him dressing up as a mermaid, she embraces it and takes him out to what looks like a mermaid parade. Love does not give the reader a lot of text, but the book is very easy to follow, and the images draw us in to what Julian is thinking and feeling. The muted colours used by Love for background images allows the focus to be drawn to the story itself and what Julian is both experiencing and imagining. The illustrations show us the feelings of the characters. Love manages to capture subtle body language to portray Julian’s emotions, such as him grabbing his arm in embarrassment when he is caught dressing up like a mermaid. The images remind one of the ocean, drawing us in to look deeper. The book reminds us that gender norms can be broken, and that anyone can be a mermaid. It is a hopeful story about love transcending normative ways of being. Children will benefit from reading this book as it will remind them that imaginations do not need to be constrained by strictly defined identity roles. Imagining possibilities of identities allows children to feel comfortable exploring identity. Highly recommended: 4 out of 4 starsReviewer: Emily Marriott
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.134 | 0.084 |
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".