The Great Cake Mystery: Precious Ramotswe’s Very First Case by A. McCall Smith
Bibliographic record
Abstract
McCall Smith, Alexander. The Great Cake Mystery: Precious Ramotswe’s Very First Case. Illus. Iain McIntosh. New York: Anchor, 2012. Print.Adult readers around the world have been charmed by the best-selling “No. 1 Ladies’ Detective Agency” series, in which Mma Ramotswe tackles the troubling mysteries and personal problems of ordinary people, and does so by relying on her sharp wit and her extraordinary insight into human nature. In this book, young readers will be introduced to a school girl who is destined to become a great detective. Here, Precious Ramotswe – “one of the nicest girls in Botswana” challenges her classmates’ assumptions in order to solve her first case. The story begins when Precious asks her beloved father to recount her favourite story: an account of the time he was “nearly eaten by a lion”. Since young Precious can tell which parts of his story really happened and which parts are made up, her father suggests that she might become a detective someday. His idea is soon put to the test when her classmates begin to notice that their lunch-time treats are being stolen from the outside shelf where they leave their bags during school. When the children scapegoat a shy boy with a sweet tooth, Precious realizes that she will need to do more than find the truth, she will need to prove it.This book has the charm of the original series, and is recommended for readers aged 7-10 years old. It offers an engaging story and several life lessons. Further, the story offers young readers a glimpse of ordinary daily life in Africa, and the author hopes it “will inspire them to read more about that wonderful continent and its remarkable people” .In a note addressed to the reader at the back of the book, the author tells us that families have been reading his “No. 1 Ladies’ Detective Agency” series aloud together, but acknowledges that the series would be challenging for young readers to read on their own, and so this book has been written with young readers in mind. Teachers and librarians who are fans of Mma Ramotswe will enjoy sharing her adventures with young readers, and will be pleased to find various curriculum materials at the back of the book.Highly recommended: 4 stars out of 4 Reviewer: Linda QuirkLinda is Assistant Special Collections Librarian at the Bruce Peel Special Collections Library at the University of 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".