Bibliographic record
Abstract
The Jerry Cans. Mamaqtuq! Illustrated by Eric Kim. Inhabit Media, 2018.Mamaqtuq! means “delicious”. This delightful Inuit board book tells a simple story of hunting all day for seal, running out of provisions and finally finding and catching a seal. It is written in Inuktitut and English, appropriately, at an early reader level. Erik Kim’s cartoon-like illustrations are bright, fun, and representative of the hunters, their clothing, and the environment. The book contains images of people using hunting rifles, but there are no images of seals being killed. As a stand-alone book it is a very good presentation of traditional hunting. However, the book is just one half of the story. The authors, The Jerry Cans, are a band from Iqualuit, whose music is a “unique mix of Inuktitut alt-country, throat singing and reggae.” The words in the Mamaqtuq! are the lyrics to a song. You can see the YouTube video at https://www.youtube.com/watch?v=DueVqYKWQxE. The piece looks like a skit, with a cardboard boat and people waving cloth to make waves. The seal is played by a young man, so the shooting part is a little more disturbing than in the book. There is also a realistic scene of lead vocalist, Andrew Morrison, eating raw, bloody meat. However, the production is exuberant, even festive, fun, and true to the culture. The book is highly recommended for elementary school libraries and public libraries.Recommendation: 4 stars out of 4Reviewer: Sandy CampbellSandy is a Health Sciences Librarian at the University of Alberta, who has written hundreds of book reviews across many disciplines. Sandy thinks that sharing books with children is one of the greatest gifts anyone can give.
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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 | 0.001 |
| 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 | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.537 | 0.400 |
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".