Bibliographic record
Abstract
White, Teagan. Counting With Barefoot Critters. Tundra Books, 2016.White’s counting book for young children begins with a good concept: make them want to turn the page. She accomplishes this by leaving a rhyme unfinished for want of a number that the listener must volunteer. This is a clever technique and will, undoubtedly, produce engagement. Unfortunately, White is not an effective poet; the rhymed couplets comprising her stanzas fail to exploit the power of verse for children.English is a language with stressed syllables. Rhythm, the arrangement of non-stressed and stressed syllables within a poetic “foot”, can draw attention to key words and concepts. It can also facilitate memory. For early readers, it can be a key to pronunciation. Combined with witty and inventive language, rhythm creates humor and/or suspense. (Theodore Geisel, “Dr. Seuss,” set the bar quite high in this regard.) Rhythm and foot in poetry can contribute to a child’s understanding of beat and measure in music, inviting a physical response. Too often, the couplets in White’s work sound rhythmically forced, as in this example-- which, incidentally, also fails as a pronunciation guide: “Surely we’ve earned a nice, peaceful rest Now that we’ve finished our daring conquest.” (Eight, [p.15])Flaws such as this weaken what could have been a superb book. White’s colored drawings are enchanting. They are detailed enough to invite the joy of discovery, but not so cluttered as to confuse. Her “Barefoot Critters” are adorable. The map that introduces their adventures is easily followed by the intended audience and is another clever way of inviting children to learn a number sequence. None-the- less, literary quality and artistic excellence should go hand-in-hand in books for children. Counting With Barefoot Critters has much of the second, and not quite enough of the first.Recommended: 3 of 4 starsReviewer: Leslie AitkenLeslie Aitken’s long career in librarianship involved selection of children’s literature for school, public, special, and university collections. She is a former Curriculum Librarian at 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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.217 | 0.131 |
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".