Bibliographic record
Abstract
Memogana, B., translator. Niqinniliurningmik. Inuivialuit Cultural Resource Centre, 2016. This small book, with its simple drawings and text accomplishes three things. It helps preserve and encourage use of the Inuvialuktun language and dialects. It situates learning materials in the day-to-day life of the children using the materials, and it preserves and passes on traditional knowledge to younger generations. Kangiryuarmiutun is one of three Inuvialuktun dialects. This volume, in Kangiryuarmiutun with English translation at the end, describes and shows the process of making dried fish. The target audience for this book is young children. The text is brief and in large print, but you really do not need the text to understand the content. Roberta Memogana’s simple pencil crayon figures stand against stark white backgrounds, each page showing a step in the fish preparation process: catching, cleaning, salting, drying, smoking and eating. The figure is a woman in a parka, often kneeling, using an ulu, or “woman’s knife”, to prepare the fish. This book should be included in school and public libraries where Inuvialuktun is spoken as well as in collections that specialize in polar children’s literature.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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.112 | 0.065 |
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".