Bibliographic record
Abstract
Liu, Alex. Little White Duck: A Childhood in China. Minneapolis: Graphic Universe, 2012. Print. This graphic memoir is co-written by author/illustrator Andrès Vera Martinez and his wife Na Liu. Martinez, an accomplished and award winning illustrator, accurately captures Na Liu’s childhood perspective of China during the 1970’s and early 80’s. Little White Duck: A Childhood in China is composed of eight insightful short stories of Na Liu and her younger sister Xiao Qin’s childhood experiences in Wuhan, China. The table of contents, glossary, timeline, map, and translations are helpful features that enable readers to gain background knowledge and context while reading. Each story in this memoir provides the reader with an opportunity to explore aspects of China’s history and traditions in a subtle yet striking visual format that complements the deeply reflective narrative voice of Na Liu. Although the stories are not directly connected, they each offer a unique perspective and understanding of Chinese culture and history. What stands out about this graphic novel memoir is more than just memories, but rather the eloquently captured events and stories that have no doubt shaped Na Liu into the person she is today. For example, when Na Liu went to visit her cousins in the countryside, she discovered that life was different there and times were tough. Although not explicitly stated, but inferred through the illustrations, the reader is left knowing that Na Liu was touched by the kindness and acceptance of her cousins and also recognized the sacrifices that her dad made to provide her with the life she had. Crisp, simple images combined with appropriate amounts of text make this an extremely accessible book for younger audiences. The wisdom and perspective Da Qin shares acknowledges that her experiences as a child set her life apart from the one her parents and others experienced. A message that transcends culture and place, and one that is important for children to consider and begin to understand centres around sacrifices that parents make, and that events that shape their lives and their identity. Highly recommended for school libraries as a multitude of connections can be made across the curriculum. It is appropriate for a wide range of grade and reading levels, and it is an excellent addition to enhance culturally responsive collections. Highly Recommended: 4 out of 4 stars Reviewer: Tamzen Kulyk Tamzen Kulyk is a teacher-librarian at two elementary schools in the Saskatoon Public School Division in Saskatoon, Saskatchewan.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".