Bibliographic record
Abstract
Kyi, Tanya L. 50 Poisonous Questions: A Book with Bite. Illus. Ross Kinnaird. Toronto: Annick Press, 2011. Print. This is the second book in the 50 questions series published by Annick Press. In this case the questions are all centered on toxins of various types such as “Can Sheep Cure Snake Bites?” and “Why Was the Hatter Mad?” It consists of eight chapters with titles such as: “Lethal Leaves”, “Murderous Villains” and “Spills and Disasters”. The answers guide young readers through a series of factoids that act as a gateway to learning about world history, the environment and life sciences. A wide range of time periods and geographical locations are covered. For example, one answer is set in 600 BC and involves how the city state of Delphi in ancient Greece defeated the city state of Kirrha by contaminating their water supply with poisonous hellebore leaves. A more contemporary example is the deadly sarin gas attack on a Japanese subway carried out by members of the Shinriko cult in 1995. There is also a significant amount of Canadian content: a deadly spider in a Manitoba classroom, mercury poisoning in Quebec and the discovery of a University of Alberta anthropologist regarding what happened to members of the ill-fated Franklin expedition. In addition to the questions, it also includes features such as the “poison puzzle” riddles to challenge readers’ powers of deduction and to reinforce what they have been learning. One particularly intriguing example is the case of the umbrella murderer involving a Bulgarian secret service agent. The author also presents information in the form of “Foul Facts” and mini-articles such as “Sprinting for Strychnine”. The book is illustrated with whimsical cartoon images on a toxic green background highlighted with skulls, cross-bones and warning signs. The look and feel is sure to pique the interest of mid to late elementary school readers and is recommended for grade four or age nine and above. The overall tone and language of the book is light-hearted and not overly academic. It does include a list of resources for further reading, a brief bibliography and an index. There are only 34 resources listed in the bibliography, which is less than one per question. However, given that the articles are designed to be brief and engaging rather than a comprehensive literature review this is not inappropriate. This book is entertaining and informative and could be used as supplementary classroom material on a variety of biology, environmental or history related topics. Recommended: 3 out of 4 stars Reviewer: Kim Frail
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.129 | 0.068 |
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".