Bibliographic record
Abstract
Wild, Margaret. The Sloth Who Slowed Us Down. Illustrated by Vivienne To, Abrams Books for Young Readers, 2018.
 You’ll want to make a speedy trip to the nearest bookstore to pick up a copy of Margaret Wild’s The Sloth Who Slowed Us Down. Together with Vivienne To’s illustrations, this simple story about how a little sloth can be a big example could make anyone want to stop and smell the roses. Life seems to speed up every day, work needs to get done faster so we have time to quickly make dinner, quickly exercise, and then quickly move on to the next thing we feel like we need to speed through. In her newest children’s book, Wild’s descriptive prose directly mirrors Sloth as he teaches Amy’s family the importance of taking our time and enjoying living in the moment. Realistically, we are all very busy, moving from one task to the next without indulging in the little things, the happy moments and the details. Everyone from busy families to teachers to even grown-ups with grown-up jobs and responsibilities could benefit from giving this adoring story a read.
 The colourful but soft illustrations created by To provide new detail and add more expression to Wild’s story each time it’s read. Illustrations of Sloth make you want to snuggle him while you read this story and feel like a child again. Through her descriptive writing, Wild portrays Sloth’s actions quite clearly. She includes phrases, such as “Sloth had a long, leisurely bath. . .” that roll off the tongue in a way that makes you feel like you’re taking your time, but in the best sort of way. 
 Highly recommended: 4 out of 4 starsReviewer: Darilyn Randall
 Darilyn Randall is a fourth-year student at the University of Alberta completing her Bachelor of Elementary Education. She is interested in teaching in a Division 1 classroom where she can incorporate children’s literacy into cross-curricular activities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".