Bibliographic record
Abstract
Fromer, Liza, and F. Gerstein. My Healthy Body. Toronto: Tundra Books, 2012. Print. Liza Fromer is a broadcast journalist with a degree in Radio and Television Arts from Ryerson University. In addition to working with The Discovery Channel and being a weekend anchor and reporter at A-Channel in Calgary, Liza has co-hosted CityTV’s Breakfast Television, hosted The Weather Network’s “Good Morning Toronto” and SLICE network’s series, “The List”. Currently, Ms Fromer lives in Toronto, as does her co-author sister-in-law, Dr. Francine Gerstein, a family physician and cosmetic medicine practitioner. Together they have co-written My Healthy Body and five other books that make up the Body Works Series. My Healthy Body opens with an author’s note about seeking medical advice for health concerns, then covers the following topics: sleep, exercise, nutrition, vaccination, eye and dental care, and the importance of family and friends, learning, and personal hygiene. Fun facts and true/false questions signal the end of each topic. Colourful illustrations depict children engaged in a variety of daily activities related to the health topics being discussed. The book focuses on the role that individuals play in being healthy. While it does not specifically situate health behaviours in a broader context of health promotion (i.e., that being healthy is affected by many factors, one of which is individual behaviour) the sections on family and friends and learning, although presented from a personal choice perspective, are a nod to some of these broader determinants. Overall, My Healthy Body is engaging and informative without being text heavy. However, it does have a few limitations. Firstly, I was surprised that, despite the book being written and published in Canada, the nutrition section does not refer to Canada’s Food Guide, highlighting the USDA’s guide instead. Similarly, the section on exercise eschews the more inclusive term, physical activity, used in the Canadian Physical Activity Guidelines. Secondly, while the publisher’s website lists the book as suitable for children ages six to nine years old, this book includes vocabulary that may be more suited to the upper end of this range and readers may need assistance to understand some of the terms. Some terms are introduced in plain language, followed by the medical term in parentheses. This treatment of health-related terminology is inconsistent – some words, such as “tissues”, “self-esteem”, “obesity” are not defined in the text, nor are they addressed in the brief glossary at the end of the book; unexpectedly, the glossary does introduce some terms that do not appear in the text (e.g., antigen). Finally, the book ends abruptly, with no conclusion, suggestions for further reading, or mention of the glossary. 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.023 | 0.016 |
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".