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Record W2493717673 · doi:10.20361/g2r61x

The Magical Animal Adoption Agency: 2 The Enchanted Egg by K. George

2016· article· en· W2493717673 on OpenAlexvenueaboutno aff
Leslie Aitken

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsGeorge (robot)Context (archaeology)Agency (philosophy)Power (physics)DramaArtMacabreLiteratureArt historySentenceHistorySociologyPhilosophyLinguisticsArchaeologySocial science

Abstract

fetched live from OpenAlex

George, Kallie. The Magical Animal Adoption Agency: 2 The Enchanted Egg. Illus. Alexandra Boiger. Toronto: Harper-Collins, 2015. Print.As this story opens, the proprietor of the Magical Animal Adoption Agency, Mr. Jams, has only recently returned from a journey, bringing with him a large, mysterious, and enchanted egg. Suddenly, he is off and away to consult with an expert on the potential nature of the egg’s unknown inhabitant. Clover, our young heroine, is left in charge of the entire Agency and its assemblage of fire salamanders, fairy horses, bewitched kittens, unicorns, and, of course, the incubating egg. Within a day of Mr. Jams’ departure, the egg hatches, unseen, and its occupant is nowhere to be found.Children will be fascinated with the detail, the drama, and the sheer unbounded imaginativeness of the world that Kallie George unfolds. They will be engaged as well with Alexandra Boiger’s black and white drawings which enhance, but do not totally define the text, leaving much to the imagination. Finally, they will relate to Clover, an ordinary little girl with extraordinary staying power.For the most part, George’s literary style is typified by imaginative vocabulary, varied sentence structure and good pacing. That being said, her writing contains some weaknesses which seem to arise in the context of colloquial usage. One example will suffice. Though dialogue is a reasonable place in which to insert a colloquialism, grammar teachers of the world will be pained by this one, “You must like animals as much as me,” said Clover.Though she has problems with spelling, Clover is, nonetheless, a remarkably clear thinker. She is also well-spoken. It would not be too much out of character for her to say, “You must like animals as much as I do.” (Dare we then to hope that her devoted readership would emulate this speech pattern? Probably not—but it’s worth a try!)If this observation seems quibbling, it stems from a noble conviction: childhood is so brief a time that what we read in its few and formative years should be the best it can be.Quibbles aside, this book would be suitable for and appealing to independent readers in the elementary grades. Primary school children would be avid listeners. All will be borne away on the magical tide of the story.Reviewer: Leslie AitkenRecommended: 3 out of 4 starsLeslie Aitken’s long career in librarianship involved selection of children’s literature for school, public, special and academic libraries. She was formerly Curriculum Librarian for the University of Alberta.

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: Other · Consensus signal: Other
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0130.006

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 head0.297
Teacher spread0.288 · 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
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".

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Citations0
Published2016
Admission routes2
Has abstractyes

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