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Record W3049761046 · doi:10.20361/dr29485

Hand Over Hand by A. Fullerton

2020· article· en· W3049761046 on OpenAlexvenueaboutno aff
Lorisia MacLeod

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)Reading (process)VocabularySimple (philosophy)Representation (politics)Media studiesVisual artsComputer scienceSociologyArtLinguisticsWorld Wide WebLawPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Fullerton, Alma. Hand Over Hand. Illustrated by Renné Benoit. Second Story Press, 2017. Award-winning author of A Good Trade and In a Cloud of Dust, Alma Fullerton returns with another excellent picture book about a young Filipina girl who goes against gender stereotypes to go fishing with her grandfather. In Hand Over Hand, Nina convinces her grandfather, Lolo, to take her out fishing and with her determination and Lolo’s support she manages to catch a large fish. The story is portrayed through simple phrases with occasional onomatopoeia in large contrasting font on Benoit’s soft watercolour images to invoke a quietly empowering story. I would recommend this book for educators and librarians not only because of the non-tokenizing nature of the representation of the Philippines or the theme of gender equality but also because of the way the illustrations and the story blend together to create a perfect storytime book for early readers to share or read alone. The illustrations are rich enough that early level readers will be entertained while the repetitive nature of the phrases and the vocabulary make it an excellent choice to grow a reader’s confidence. It also has the potential to be laddered into an activity where learners create a story of their own and use watercolours to illustrate their story which could appear to higher-level educators looking for an English and/or Art project for their classes. Highly recommended: 4 out of 4 starsReviewer: Lorisia MacLeod Lorisia MacLeod is the Online Reference Centre Coordinator with The Alberta Library (TAL) and a proud member of the James Smith Cree Nation. When not working on indigenization or diversity in librarianship, Lorisia enjoys reading almost any variation of Sherlock Holmes, comics, or travelling.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.617
Threshold uncertainty score0.546

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.6170.445

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 head0.009
GPT teacher head0.266
Teacher spread0.258 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes2
Has abstractyes

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