Bibliographic record
Abstract
Flaherty, Louise. The Gnawer of Rocks. Illustrated by Jim Nelson. Inhabit Media, 2017. The Gnawer of Rocks, written by Louise Flaherty and illustrated by Jim Nelson, is based on the author's memories of a story she heard as a child from an Inuk storyteller, Levi Iqalugjuaq, in Nunavut in the 1970s. The book, which feels like an incredible mix of picture book and graphic novel, focuses on a traditional story about a creature called Mangittatuarjuk and two young women who fall into her clutches. Nelson's artwork follows the layout of a comic book, using word balloons and panel captions, which makes for an immersive reading experience following two girls who discover a trail of beautiful rocks outside of camp which lead them from the bright and colourful world of home into the increasingly dark and frightening world of Mangittatuarjuk. The book mixes Inuktitut terms throughout, but does include a glossary at the end. The story does get both gruesome and horrific in the cave of Mangittatuarjuk, but the story, which would be great for older school children, does include a warning in the author's note. A really great introduction to traditional northern Canadian stories, the book includes an introduction for context and acknowledges the original storyteller as well as the reasons for this type of story and its likely role in the lives of children. An excellent read for children who are already comfortable with scary stories. Highly recommended: 4 out of 4 starsReviewer: Kirk MacLeod Kirk MacLeod is the Open Data Team Lead for the Government of Alberta’s Open Government Portal. A Life-Long reader, he moderates two book clubs and is constantly on the lookout for new great books!
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 | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.143 | 0.080 |
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".