Bibliographic record
Abstract
Hartt-Sussman, Heather. Noni is Nervous. Illus. Geneviève Côté. Toronto: Tundra Books-Random House of Canada, 2013. Print.Noni is anxious about many things but most of all she is nervous about her first day of school. Among her school jitters are: what to wear, whether or not her teacher will be nice, and where to sit. To calm her nerves, Noni is constantly talking, biting her nails, and twirling her hair. After her first day her mother advises her to make a friend. Despite her nervousness, Noni introduces herself to an outgoing girl named Briar on the bus who then introduces Noni to many other children. Noni comes home feeling more confident and calm.Noni is Nervous is a cute book about adapting despite being nervous. Between Hartt-Sussman’s repetitive prose and Côté’s fitting illustrations the reader is always clear on how the characters are feeling. The story transitions well from depicting Noni’s nervousness to her confidence. I particularly liked how though Noni had befriended Briar she was still nervous about a few things en route to school as opposed to friendship being an instant cure. She does develop some confidence and is able to spunkily tell her family that there is nothing to be nervous about. Children will be able to see that though they may be nervous there isn’t always a need and things will be okay.I would have liked to see more of the story devoted to Noni overcoming her anxiety than is shown in the book. There was also a spelling mistake in the book, though I doubt children will catch it.Recommended: 3 out of 4 starsReviewer: Brittany GregsonBrittany Gregson is a graduate of MacEwan University’s Library and Information Technology program.She works at the Family and Community Resource Centre, Alberta Children’s Hospital as the Child Health Information Specialist. Other than reading she enjoys both baking and crafting.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.023 |
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".