Bibliographic record
Abstract
Uluadluak, Donald. The People of the Sea, illustrated by Mike Motz, Inhabit Media, 2017The People of the Sea is a recollection by the late Inuit elder, Donald Uluadluak, of seeing an arnajuinnaq or a sea person, while he and his friends played on the beach near Arviat. The story is a simple retelling of the adventure which highlights the presence of sea-people in Inuit culture. Unlike the vicious mermaids or tuutaliit of books such as Kiviuq and the Mermaids, who have frightening appearances and want to destroy kayaks and kill hunters, the sea-people in this story seem benign and simply curious. Mike Motz has drawn them as almost-expressionless creatures who look like fair-skinned women with long dark hair and facial tattoos – just as Uluadluak describes them. The two-page images are multi-coloured and do a good job of reflecting the sea and tundra environments. Text is overprinted on the images. The text is simple and comprehensible to the intended audience of 5 to 7 year-olds, but is above their reading level, so an adult would need to read this book aloud. The People of the Sea would also be appropriate for upper elementary children who are interested in traditional myths and legends. Highly recommended for school libraries and public libraries. Highly Recommended: 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 | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.053 | 0.031 |
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".