Bibliographic record
Abstract
Pyle, C. Kevin. Take What You Can Carry. New York. Henry Holt and Company LLC, 2012. Print. This graphic novel intertwines two different stories, set four generations apart. The two stories are told in alternating perspectives of the two main characters, Ken and Kyle. To emphasize and distinguish between the two different stories, Pyle uses two diverse colors to set them apart. Ken’s story, in sepia tones, is set in 1941 when his family is sent to a Japanese Internment camp. Kyle’s story, in blue watercolor, takes place in 1978 in Chicago when he moves to a new neighborhood, is making new friends and rebelling against his father. At the beginning it seems as though the two stories may never connect. Ken’s family has been uprooted from their home, his father is placed in jail, and he and his family are taken to an internment camp where they are treated like animals. Ken is faced with many decisions and choices about how to deal with his new life. Similarly, Kyle’s new friends begin stealing and they all become more reckless. Although Ken and Kyle’s worlds are vastly different, they are both faced with strikingly similar choices. Both teenagers are able to rise above, with the help of a wise adult, and take responsibility for their actions, and discover compassion and loyalty despite the hardships faced. Ken’s story has no narration or text, only pictures. This requires the reader to rely on the images to infer and make meaning from them. As a result, Ken’s story can be difficult to understand and necessitates an experienced visual reader with an ability to draw conclusions from images, and a reader interested enough to reread sections. Historical notes are provided at the end of the story to fill in the gaps and provide further context for the reader. Despite the shortcomings of having to put the pieces together, it does challenge the reader to think critically about this time in history and make connections to current day society. A thought provoking read, with important messages for all ages about forgiveness and finding happiness even in the most destitute of situations. Recommended for school library collections. Recommended: 3 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.345 | 0.298 |
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".