Bibliographic record
Abstract
Davies, Nicola. The Day War Came. Illustrated by Rebecca Cobb. Somerville, Massachusetts, Candlewick Press, in association with Help Refugees, 2018. A young school girl begins her day happily by breakfasting with her family, walking to school with her mother, and commencing the normal, pleasant learning activities of her classroom. In an instant, her world changes; she is orphaned and alone in a devastated landscape. War has come; she articulates its reality: “War took everything. War took everyone. I was ragged, bloody, all alone.” Simple, forceful, poetic lines such as these carry forward this story of a child refugee. Though it could be read and understood by primary school children, it would resonate with readers young and old alike. Nicola Davies indicates that her book was inspired by the Guardian newspaper website which featured an account of a refugee child who was refused school entry because there was no chair for her to sit on. In Davies’ own words: “…hundreds and hundreds of people posted images of empty chairs, with the hashtag #3000 chairs, as symbols of solidarity with children who had lost everything and had no place to go.” Davies’ interpretation of this reality for young readers is engrossing and moving. Her storyline is perfectly interpreted by the watercolour and graphite pencil illustrations of Rebecca Cobb. Using an expressionistic style, Cobb captures the feelings of confusion and disbelief, abandonment and isolation felt by the displaced child. She also brings a sense of hope to the story’s conclusion. The teamwork of Davies and Cobb is brilliant. Together, they have created a moving and memorable piece of children’s literature. Highly recommended: 4 out of 4 starsReviewer: Leslie AitkenLeslie Aitken’s long career in librarianship included selection of children’s literature for school, public, special and academic libraries. She is a former Curriculum Librarian of 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.091 | 0.061 |
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".