Bibliographic record
Abstract
Winters, Kari-Lynn. Gift Days. Illus. Stephen Taylor. Markham, ON: Fitzhenry & Whiteside, 2012. Print.A young Ugandan girl, Nassali, watches her brother go to school every day, and wishes she could go too. She wants to learn to read but her time is filled with taking care of her family, her responsibility since the death of her mother. How her life changes, and how she learns to read is told through this picture book. The author, Kari-Lynn Winters, is a Canadian author and literacy researcher and a faculty member in Teacher Education at Brock University. She is a well-known author of numerous picture books.The book is illustrated by Stephen Taylor, a graduate of the Ontario College of Art, and frequent Illustrator of children’s books. The illustrations are charming and add a great deal of depth to the story. They do an excellent job of conveying how alone and left out Nassali feels as her brother goes to school every day, and her joy and sense of pride when she learns to read.The story unfortunately, is not as engaging as the illustrations. The language is quite dry and somewhat didactic, seemingly at odds with the picture book format. There are some disconnections in the story. It is unclear, for example, why the brother decides to teach Nassali to read. For this reason it is difficult to determine the intended audience. The format suggests primary school students, but the content suggests an older audience.This book would be useful as an instructional resource in an elementary school setting for a unit on gender issues or development. It is not, however, likely to engage a self-directed reader of any age.Reviewer: Margaret Law Recommended with reservations: 2 out of 4 starsMargaret Law is the Associate University Librarian (International Relations) at the University of Alberta, responsible for developing international library partnerships. Previously, she was a public librarian, primarily involved with the development of rural libraries in 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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.313 | 0.231 |
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".