Bibliographic record
Abstract
Reviewed by: Skraelings by Rachel Qitsualik-Tinsley April Spisak Qitsualik-Tinsley, Rachel Skraelings; written by Rachel and Sean Qitsualik-Tinsley; illus. by Andrew Trabbold. Inhabit, 2014 87 p Paper ed. ISBN 978-1-927095-54-6 $10.95 R Gr. 4–6 This brief novel that draws from traditional oral storytelling elements features Kannujag, a fictional Inuit hunter who may know nothing of the modern life the reader experiences a thousand years later (as the narrator explains), but who is deeply informed about the nomadic hunting life of the Inuit. Mostly the Inuit and Tuniit people in his region steer clear of one another (to the extent that legends in each group suggest the others aren’t quite human), but Kannujag’s ethics don’t allow him to just ignore a scene he stumbles upon: a Tuniit village under siege by ominous men in boats. His involvement will leave him permanently changed. The story’s conclusion offers insight into the fact that the invaders were Vikings, the location was Greenland, and Kannujag’s fears that there would never be peace again in his life weren’t quite borne out, but future generations would certainly suffer under colonization. The authors adroitly balance fiction, legend, and nonfiction, and they package it all with the perfect knowing narrator who has plenty of asides to keep readers on track and up to speed, while never breaking the flow of the story itself. Most chapters are accented with a brooding black-and-white illustration that primarily emphasizes the stark gravity of what the protagonists face. While a deep understanding of this text will certainly be enhanced by cruising through the glossary or knowing at least a bit about Inuit cultures, the story itself is gripping, haunting, and elegantly told, and it can stand alone even for readers who resist all efforts at contextualization; it could also partner interestingly with Dorris’ Morning Girl (BCCB 10/92). End matter includes a pronunciation guide and extensive glossary. Copyright © 2014 The Board of Trustees of the University of Illinois
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.054 | 0.028 |
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".