Bibliographic record
Abstract
Torres, J. & Hicks, Faith Erin. Bigfoot Boy: Into the Woods. Toronto: Kids Can Press, 2012. Print. As a child growing up in a small mountain town, the mystery of the Sasquatch captured my imagination. I searched for him whenever we explored in the woods behind our house, and imagined this creature watching us through the windows at night. So I was delighted to read this collaboration between writer J. Torres and illustrator Faith Erin Hicks, a graphic novel that will appeal to readers of all ages. The story begins when ten-year-old Rufus is dropped off at his grandmother’s house for the long weekend. He becomes bored and decides to explore the woods, where he meets a girl named Penny and follows her deep into the woods. The discovery of a legendary totem, inscribed with a special word, provides Rufus with special powers and a magical adventure involving a Sasquatch that he will never forget. The story, although simply told, conveys humour, mystery, and a sense of wonder as Rufus and Penny must overcome obstacles and scheming enemies. Character dialogue is authentic as to how a ten-year-old would speak, and the illustrations by Hicks enhance the humour and charm of the story. From Rufus, the freckle-faced lead, to the feisty Penny who does not slide into a stereotype of a First Nations character, their expressions and interactions feel real and the forest setting simultaneously magical and sinister. Recommended: 3 out of 4 stars Reviewer: Shelly Jobagy Shelly Jobagy is a teacher-librarian and administrator at a K-9 school in Edmonton, Alberta.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.070 | 0.032 |
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".