Bibliographic record
Abstract
Pingo, Anna. Aluniq: and her friend, Buster. Illus. Karleen Green. Inuvilauit Settlement Region, 2016.This is a simple story about separation of loved ones, a common, but none-the-less painful necessity in many remote communities. Aluniq is a little girl who lives with her Norwegian grandparents at the Qunngilaat Reindeer Station in Canada’s Northwest Territories. Aluniq has a pet reindeer calf named Buster. She has lived with her grandparents from birth because her mother has been away for years for tuberculosis treatment. Now that her mother is well and back in Tuktuuyaqtuuq, Aluniq must go to live with her parents, hundreds of kilometers away from the Station. But “Aluniq [is] frightened as she [doesn’t] know who these people [are].” Her grandparents are very sad to be separated from her and she is sad to be separated from them and from Buster. Although Aluniq does not recognize it at the time, this is also a story of reunion and of putting things right. Her parents are happy to have her return. This simple, but realistic story highlights the fact that many families in the Inuvialuit Settlement Region and other remote parts of Canada have been disrupted when people have had to leave home to receive medical treatment. It is clearly written and readable at an upper elementary level. Karleen Green’s drawings are rustic and unsophisticated, but are delightfully representative of the Inuit world and accessible to children. Available in English, as well as all three Inuvialuktun dialects, these books are appropriate for elementary school and public libraries and any collection of Canadian children’s literature.Highly recommended: 4 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.173 | 0.039 |
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".