Bibliographic record
Abstract
Bowers, Vivien. Hey Canada!. Toronto: Tundra Books, 2012. Print. Born in Vancouver, Canada, Vivien Bowers received her Bachelor of Arts from the University of British Columbia (BC). She has taught at the elementary school level and currently works as a freelance writer in BC and has written for children and adult audiences alike. She has authored elementary and secondary school materials, non-fiction books and magazine articles. Hey Canada! follows Alice, her grandmother, her cousin Cal, and his hamster, simply named ‘Hampster’, on a car trip across Canada. As the family travels through each province and territory, the reader is introduced to geographic, historical, and culturally significant locations, activities, and foods. As a nod to current technology, the content is narrated from the perspective of seven-year-old Alice, in the form of blog posts with highlight boxes featuring her cousin’s tweets sprinkled throughout the book. A map of Canada shows readers the path travelled by Alice, Cal, Grandma and Hampster as they journey from east to west. Hey Canada! presents colourful, cartoon-style illustrations interspersed with photos. The addition of comic strip styled interludes depicting historical events and fun facts make the content engaging and fun to read. Each province and territory is introduced with an illustration of the provincial flower, bird, and an outline of the province with the capital city highlighted. Unfortunately, the provincial flower for Alberta is incorrectly listed as White Trillium instead of Wild Rose, and the Museum of Civilization is described as being located in Ottawa instead of in Hull, Quebec. Hopefully, these errors will be corrected in the next edition. Readers who enjoy Hey Canada! and who are not familiar with the author’s earlier books may want to check out Wow Canada! and That’s Very Canadian for equally entertaining and informative reading about this country. Recommended: 3 out of 4 stars Reviewer: Maria TanMaria is a Public Services Librarian at the University of Alberta’s H. T. Coutts Education Library. She enjoys travelling and visiting unique and far-flung libraries. An avid foodie, Maria’s motto is, “There’s really no good reason to stop the flow of snacks”.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.321 | 0.216 |
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".