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Record W4251158034 · doi:10.1353/bcc.2015.0661

A Handful of Stars by Cynthia Lord (review)

2015· article· en· W4251158034 on OpenAlexaboutno aff
Deborah Stevenson

Bibliographic record

VenueBulletin of the Center for Children's Books./Bulletin of the Center for Children's Books · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInterdisciplinary Cultural and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStarsAstronomyArtPhysics

Abstract

fetched live from OpenAlex

Reviewed by: A Handful of Stars by Cynthia Lord Deborah Stevenson Lord, Cynthia A Handful of Stars. Scholastic, 2015 [192p] Trade ed. ISBN 978-0-545-70027-6 $16.99 E-book ed. ISBN 978-0-545-70029-0 $16.99 Reviewed from galleys R* Gr. 3-5 It’s a dog that brings Lily and Salma together: when Lucky, Lily’s ancient blind Labrador retriever, bolts for the road, Salma, one of the migrant workers picking Maine blueberries, lures him to safety with her sandwich. Soon a friendship blossoms between the two twelve-year-olds, and artistic Salma helps Lily decorate crafted bee houses to sell at the blueberry festival in order to raise funds for cataract surgery for Lucky. Salma also decides to enter the Downeast Blueberry Queen pageant, a move that breaks racial barriers but puts Lily, whose best friend is trying for a repeat victory, in an awkward position. Lord writes with a quiet naturalness that allows multiple plot facets to emerge without becoming messagey or heavy-handed. The treatment of Salma’s migrant life is matter-of-fact but direct, and Lily plausibly deals [End Page 35] with possibilities of local racism and swells with indignation on behalf of her new friend. Motherless Lily’s occasional longing for a maternal figure (“It made me all messed up inside to have someone treat me like a daughter”) is poignant, and her eventual Salma-encouraged shift in her approach to Lucky fits smoothly with her character growth. It’s the straightforward and unaffected prose (highly suitable for a readaloud as well as reading alone) that really allows Lily’s story to shine, though, and it’s hard to resist joining her on her journey toward greater maturity. Copyright © 2015 The Board of Trustees of the University of Illinois

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)0.005
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: Review · Consensus signal: Review
Teacher disagreement score0.058
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0580.037

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 head0.017
GPT teacher head0.260
Teacher spread0.243 · 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
GenreReview

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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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