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Record W2792993107 · doi:10.20361/g2mh4x

The Caterpillar Woman by N. Sammurtok

2018· article· en· W2792993107 on OpenAlexvenueaboutno aff
Sean Borle

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsMAGIC (telescope)KindnessCaterpillarCharacter (mathematics)PicnicPsychologyVisual artsArtAestheticsPhilosophyEcologyMathematics

Abstract

fetched live from OpenAlex

Sammurtok, Nadia. The Caterpillar Woman. Inhabit Media, 2016In The Caterpillar Woman, Nadia Sammurtok tells a traditional Inuit version of “the princess and the frog” story. A kind young woman, Piujuq, trades coats with a woman who is cold. When she puts on the other woman’s coat she turns into a caterpillar. She lives alone because she thinks that no one will want to be around her until an older hunter sees past her strange exterior and marries her. Through the magic of an ancient drum beater, they are “rewarded for their kindness and unconditional love” and become young, strong and beautiful again. The language is too difficult for a picture book, so an older person would need to read this to small children. While the cover design is strangely uninviting and sad, not making the reader want to pick up the book, the rest of the illustration is well done. The pictures convey creepiness where appropriate, such as the darkness of the inside of a tent at night and many sweeping tundra landscapes.In the same way that this book’s cover is not a good representation of its content, the main health message in this book is “don’t judge a book by its cover” or learn to look past superficial physical differences to see the person, their character, and their abilities. The secondary message is that we should be kind to people, no matter what their appearance. These are good lessons for young children to learn. I highly recommend this book for as a starting place for classroom discussions on physical differences.Highly Recommended: 4 stars out of 4Reviewer: Sean BorleSean Borle is a University of Alberta undergraduate student who is an advocate for child health and safety.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.325

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0970.073

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 head0.010
GPT teacher head0.340
Teacher spread0.330 · 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".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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