Bibliographic record
Abstract
Barnett, Mac, and Jon Klassen. Sam & Dave Dig a Hole. Somerville, Massachusetts: Candlewick Press, 2014. Print.Sam and Dave are on a mission to find something spectacular. They head out with shovel in hand to dig a hole. The digging is hard work but the determined duo makes progress. Pretty soon the hole is deeper than they are tall, and they rest over animal crackers and chocolate milk to strategize: should they continue downwards? Left? Right?This delightful story works hand-in-hand with the clever illustrations of Jon Klassen, revealing only to the reader, the spectacular things that Sam and Dave are missing as they change directions in their digging. My co-reviewer (a six-year-old niece) was wrought with frustration and giggles to see the gems and treasures that were passing Dave’s and Sam’s notice as they changed directions.In a clever way Mac Barnett has found a way to not only tell an entertaining story, but to also teach about choices and consequences. After the first reading, the co-reviewer and I discussed how the story might have been different if Sam and Dave had not changed directions. Klassen’s washed-out brownish images convey a beautiful underground world of dirt and gems.This book is best suited for children who are at least 5-6 years old, as they need to be able to understand the story as well as read the illustrations to understand it completely. Another co-reviewer (a 3-year old niece) was delighted with the illustrations but did not take away the same level of enjoyment and pleasure as her older sister. This book was a wonderful read.Highly recommended: 4 out of 4 starsReviewer: Hanne PearceHanne Pearce has worked at the University of Alberta Libraries in various support staff positions since 2004 and is currently a Public Service Librarian at the HT Coutts Education and Physical Education Library. Aside from being an avid reader she has continuing interests in writing, photography, graphic design and knitting.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.135 | 0.080 |
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".