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Record W2337676931 · doi:10.20361/g2j30n

Voices from the Wild: An Animal Sensagoria by D. Bouchard

2016· article· en· W2337676931 on OpenAlexvenueaboutno aff
Linda Quirk

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2016
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryPortraitTastePaintingAppealArt historyPower (physics)ArtValue (mathematics)SociologyLiteratureLawPsychologyPolitical science

Abstract

fetched live from OpenAlex

Bouchard, David. Voices from the Wild: An Animal Sensagoria. Paintings by Ron Parker. Markham, ON: Fitzhenry & Whiteside, 2013. Print.This gorgeous book brings together two extraordinarily-talented individuals. David Bouchard is a former teacher, a former president of the Metis Nation of Greater Victoria, a recipient of the Order of Canada, and the author of many books. His popular books use poetry, prose, and visual elements to explore Aboriginal and Métis culture and traditions in both French and English. Ron Parker is one of Canada’s best wildlife artists. His career took off in the 1990s when his realistic portraits of animals in their natural habitats stood alongside those of Robert Bateman and helped to create a very hot market for signed limited edition prints. The publisher is to be applauded for thinking of bringing together Parker’s glorious paintings and Bouchard’s inspiring poetry. It was a wonderful idea, but, unfortunately, it was not well executed. It is most unfortunate that Parker’s beautiful images were not packaged in a fresher and more contemporary book design, one that would appeal to today’s young people. The author says that he “wrote this book with young people in mind” and certainly he has organized his poetry into a familiar scheme for a children’s book—sections which explore the five senses (sight, hearing, touch, smell, and taste)—but unfortunately, the scheme is too childish for young adults while the poetry is too sophisticated for small children. There is great value and power in this poetry, in which the reader is asked to see the world through the senses and perspectives of numerous animals, but, just who is the intended audience?As it is, this volume does a disservice to both the author and the artist. The design may be appealing to parents or teachers of a certain age—who may feel a nostalgic affection for its familiar, if outdated, style, and who will be undaunted by the poetry—but the publisher has made a mistake in marketing this title as a children’s book. As it is, this book stands outside of normal publishing categories. Although too small to be classified as a coffee table book, both the design and the content seem more aligned with that category than any other. Although there is a great deal to applaud here, I cannot recommend this as a children’s book.Not recommended: one star out of fourReviewer: Linda QuirkLinda taught courses in Multicultural Canadian Literature, Women's Writing, and Children's Literature at Queen's University (Kingston) and at Seneca College (Toronto) before moving to Edmonton to become the Assistant Special Collections Librarian at the Bruce Peel Special Collections Library at the University of Alberta. Her favourite children's book to teach is Hana's Suitcase, not only because Hana's story is so compelling, but because the format of this non-fiction book teaches students of all ages about historical investigation and reveals that it is possible to recover the stories of those who have been forgotten by history.

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)0.001
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: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0050.006
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0170.007

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 head0.013
GPT teacher head0.341
Teacher spread0.328 · 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".

Quick stats

Citations0
Published2016
Admission routes2
Has abstractyes

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