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Record W2580094011 · doi:10.20361/g2260b

Noni Speaks up by H. Hartt-Sussman

2017· article· en· W2580094011 on OpenAlexvenueaboutno aff
Maria Tan

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPsychodrama and Leishmaniasis Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMisfortuneCouragePsychologyArtPsychoanalysisMedicineVisual artsPhilosophyTheology

Abstract

fetched live from OpenAlex

Hartt-Sussman, Heather. Noni speaks up. Tundra Books, 2016.Nominated for the Ontario Library Association’s Blue Spruce Award, Noni speaks up is the third book in the Noni series by Toronto-based children’s picture book author, Heather Hartt-Sussman, and acclaimed illustrator Geneviève Côté.When Noni sees Hector being bullied by other kids at school, and is encouraged by her friends to join in, she is unable to speak up; Noni is paralyzed by fear of making enemies if she stands up for her schoolmate. Noni feels bad for not defending Hector, but is uncertain about what to do.During a restless night, she worries about what might happen if she doesn’t take her friends’ side. She considers the things Hector is being bullied about. As Noni reflects on her relationships with her friends, she notices that they sometimes say and do things to her that are hurtful.When Noni goes to school the next day, she sees Hector being bullied again and experiences the same fear and inability to speak. But when her friend laughs at Hector’s misfortune, Noni has had enough and screws up the courage to defend Hector. Speaking out stops her friend laughing, and Noni and a grateful Hector actively ignore the bully’s taunting, demonstrating another strategy for dealing with bullying.Noni speaks up presents a realistic scenario and provides accurate, helpful information for dealing with bullying, in an empathic and reassuring manner. Young readers will relate to the events in the story, and the Noni models positive behaviour that children experiencing a similar issue could put into practice. This book meets the Juvenile Health Fiction Checklist criteria (described in the October 2014 issue of the Deakin Review).Readers who enjoy Noni speaks up can re-connect with Noni in Hartt-Sussman’s other books, Noni is nervous and Noni says no.Recommended: 3 out of 4 starsReviewer: Maria TanMaria is a sessional instructor at the University of Alberta and a former editorial team member of the Deakin Review. She is the co-author, with Sandy Campbell, of the Children’s Health Fiction Checklist, described in the October 2014 Special Issue of the Deakin Review (Vol. 4, No. 2) https://ejournals.library.ualberta.ca/index.php/deakinreview/article/view/23321.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.734
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.333
Teacher spread0.318 · 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 teacher head, not a consensus.

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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