Bibliographic record
Abstract
Horvath, Polly. One Year in Coal Harbour. Toronto: Groundwood Books, 2012. Print. In this sequel to the multiple award winning, Everything on a Waffle, Horvath’s signature quirky humour and insights into human nature emerge once more as we follow 12-year-old Primrose Squarp’s attempts at matchmaking, at finding a best friend, and at generally trying to make life turn out right. The lovable Evie and Bert, who took Primrose in when her parents were lost at sea, sensible Uncle Jack, the entrepreneur who returned to Coal Harbour to look after Primrose, and fiercely independent Miss Bowzer, Primrose’s confidant and owner of The Girl on the Red Swing where everything is served on a waffle, return from the first book to help Primrose navigate life as a ‘tween’ in Coal Harbour. In one year, Primrose learns about defending what she cares about, letting people make their own choices, and accepting the flaws in herself as well as others. Primrose faces some hard lessons but readers will be glad to know that everything turns out, if not perfectly, then as it should, in the end. Horvath broaches issues related to foster children, unfit parents, environmental protests, relationships, and grieving, with honesty and empathy, showing real respect for her young readers’ ability to understand the nuances of these situations. Her characters embody the quirkiness and wisdom of small town life, making them even more believable. Each chapter begins with “What Happened...” or “What Didn’t Happen...” leading the reader along through the traumatic events of Primrose’s year in Coal Harbour, and ends with a recipe Primrose collects for the local cookbook she is writing bringing the tale back to the comfort zone of mundane details. With this marvelous glimpse of the world from the eyes of a 12-year-old girl, peppered with high hopes, frustration, insight and humour, Horvath has done it again. She has left me wanting more. Highly recommended: 4 out of 4 stars Reviewer: Kathy Inglis Kathy Inglis is a teacher-librarian and kindergarten teacher at South Park Family School in Victoria, BC and a Masters student in the Teacher-Librarianship through Distance Learning Program at the University of Alberta. Her favourite part of the job is seeing the excited look on the faces of students who have found that perfect book.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.105 | 0.067 |
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".