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Record W2765393493 · doi:10.20361/g2kq39

Outstanding in the Rain: A Whole Story With Holes by F. Viva

2017· article· en· W2765393493 on OpenAlexvenueaboutno aff
Stephanie Borle

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSlangSentencePicture booksSimple (philosophy)Style (visual arts)White (mutation)Visual artsComputer scienceArtArt historyHistoryLinguisticsArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

Viva, Frank. Outstanding in the Rain: A Whole Story With Holes. Tundra Books, 2015.Frank Viva is an illustrator and designer, so design, rather than storyline, is the strength of this work. The illustrations are a simple, retro-modern, cartoon-like style. Viva uses a palette of five tints: blue, yellow, red, brown, and white. This gives Outstanding in the Rain a “vintage” look.This children’s picture book is a collection of oronyms, words or phrases that sound the same but have different meanings, woven into a simple story about a boy’s trip to the amusement park. For each oronym pair, Viva incorporates a die-cut hole into the text. Words from the following page are shown as part of the sentence of the page being read. When you flip the page, the die-cut reveals a different picture and the second part of the oronym is also revealed. For example, the words “night rain” in the phrase “The night rain is just beginning to fall” turn into “night train” in the text of next page, “The night train is coming-I hear its call”. The combination of die-cuts, oronyms, and rhyme is complex and clever. Even the title and subtitle, “Outstanding in the rain” and “A whole story with holes”, both include plays on words.Children will have fun playing with the words in the same way that Viva has played with them. This book would be a great tool for teachers to introduce having fun with language, specifically oronyms. Upper elementary children would have the most fun with the double meanings, but even adults would enjoy this book.Highly recommended: 4 stars out of 4Reviewer: Stephanie BorleStephanie Borle is a University of Alberta student of linguistics who enjoys working with children and new immigrants. She spent a year teaching English as a Second Language in Japan to kindergarten and junior high school students.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0040.006
Open science0.0010.003
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0150.008

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.

Opus teacher head0.011
GPT teacher head0.247
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes2
Has abstractyes

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