Bibliographic record
Abstract
Gutnick, David. Mr. Mergler, Beethoven, and Me. Illustrated by Mathilde Cinq-Mar. Toronto: Second Story Press, 2018. In this lovely picture book, David Gutnick explores an episode in the life of Canadian music teacher, Daniel Mergler. The first person narrator of the story is a musically gifted young girl whose family has emigrated from China. Like many immigrant families, hers is struggling financially; there is no money for music lessons. By chance, the girl and her father meet Mr. Mergler during a pleasant outing in a park. The encounter leads to the child’s musical instruction and, as well, her enduring affection for Beethoven. Gutnick concludes his book with end notes: the first leaves no doubt as to the giftedness, kindness, and generosity of Daniel Mergler; the second, a brief biography of Ludwig van Beethoven, will be helpful to young readers unacquainted with classical music. Because the author claims to be only “inspired by” a true story, we must assume that at least some of the specific details of the plot are fictionalized. Still, the book is based on a CBC documentary, “Beethoven’s Bust,” which Gutnick prepared for broadcast (it was aired as a segment of the CBC radio program, “The Sunday Edition” in 2014). However fictionalized, the story seems real. Interestingly, the child narrator is never named—perhaps because she is a composite figure, perhaps because Gutnick wishes to protect the privacy of his “sources.” Nonetheless, through the delicate drawings of Mathilde Cinq-Mar, we, the readers, come to know this child: we feel her sense of bliss as she flies through the air on a swing in the park; we admire her determination and certainty as she carols “Oh Susanna…” in her “audition” for Mr. Megler; we understand her rapt delight as she begins to master the piano keyboard, producing sounds that “…make everything else disappear.” An inspired touch is Cinq-Mar’s use of musical staves to create curved and sweeping pathways into the illustrated pages. The technique results in a perfect marriage of artwork and text. In sum, Mr. Mergler, Beethoven, and Me is a well-crafted, captivating, and heart-warming book that would be very suitable for independent readers in the upper primary and elementary grades. Reviewer: Leslie AitkenHighly recommended: 4 out of 4 stars Leslie Aitken’s long career in librarianship included selection of children’s literature for school, special and academic libraries. She is a former Curriculum Librarian of 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.104 | 0.037 |
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".