Bibliographic record
Abstract
Kalluk, Celina. Sweetest Kulu. Illus. Alexandria Neonakis. Iqaluit, NU: Inhabit Media Inc., 2014. Print.“Kulu” is an Inuktitut term of endearment for babies and small children. In this work, traditional throat singer and author, Celina Kalluk, shows all of the gifts that nature brings to a newborn baby. The images show the baby cradled and adored by many creatures. Each creature brings a character trait as a gift for the baby. “Caribou chose patience for you, cutest Kulu. He gave you the ability to look to the stars, so that you will always know where you are and may gently lead the way”. With each gift, Kalluk uses a different adjective to describe the baby – happy Kulu, admired Kulu, beloved Kulu. Illustrator, Alexandria Neonakis has created an image for each animal in rich and deep colours. The images spread over two facing pages with text over-printed. Each image is gentle and tender. The baby is shown nestled between the front hooves of a musk-ox, curled up against a polar bear or snuggled up in the paws of an Arctic hare. The baby is reflected in the water when the Arctic char brings a gift of tenderness.This book is a beautiful representation of a mother’s love for her baby reflected in the traditional Inuit connection to the land and nature. It is a calming and peaceful book, which will become a bedtime read-aloud favourite. Highly recommended for elementary school libraries, public libraries and babies’ rooms everywhere.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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.340 | 0.335 |
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".