Bibliographic record
Abstract
Qaunaq, Sakiasi. The Orphan and the Polar Bear. Iqaluit: Inhabit Media, Inc., 2011. Print.One of the common themes in Inuit stories is that of the orphan child alone on the land. In this version, told by Arctic Bay elder Sakiasi Qalinaq, who learned his stories from his grandmother, the orphan is abandoned by hunters from his village and adopted by a village of polar bears. The bears teach him to hunt and survive on the land and, when he is grown, return him to his people. The image on the cover of the book showing the child riding the polar bear is an iconic one. This mythological relationship between child and polar bear is also found in non-Inuit literature, most notably in Philip Pullman’s The Golden Compass. In the bears’ village the orphan is trained to hunt and survive on the land. The bears also teach him their traditional wisdom. For example, when one of the bears wants to go “push down” some humans because they “look so silly standing on their skinny legs”, a wiser elder bear says, “Never talk that way…don’t make humans our enemy. Stay clear of them and their camps.” The book is primarily a picture-book. Unlike many of the other books of Inuit legends published by Inhabit Media, the pictures are not scary. Rather they are quite beautiful. The extra width of the landscape format gives artist, Eva Widermann, the opportunity to spread her illustrations across two pages reflecting the wide expanses of the Arctic. Text usually takes up one corner or a few lines of a page. Widermann’s images are realistic. However, because this story is from a time when animals could shape-shift into human form, she sometimes gives the bears human postures and gestures. For example, in the image on page 15, the polar bear is standing with a harpoon grasped in its front paws, handing it to the orphan. Bears are also shown in their human form in three images. In the image on page 20, depicting the inside of an igloo in the bears’ village, a woman with human form is tending the fire.Overall this is a lovely rendition of the story. While designed for an elementary school audience, anyone with an interest in traditional Arctic tales will enjoy it. Recommended for elementary schools and public libraries. Recommendation: 4 out of 4 starsReviewer: 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 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.025 |
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".