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Record W170788769 · doi:10.20361/g2hs3c

The Sea Wolves by I. McAllister

2012· article· en· W170788769 on OpenAlexvenueaboutno aff
Sandy Campbell

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2012
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsFish <Actinopterygii>ParallelsHistoryStatement (logic)FishingEnvironmental ethicsEcologyLawFisheryPhilosophyPolitical scienceBiology

Abstract

fetched live from OpenAlex

McAllister, Ian, and Nicholas Read. The Sea Wolves: Living Wild in the Great Bear Rainforest. Vancouver: Orca, 2010. Print At first glance, The Sea Wolves is a small coffee table book. It is not, however, just a pretty photographic exploration of the wolves that inhabit The Great Bear Rainforest. It is a very long opinion piece written expressly to convince readers that wolves are not “the big bad wolf” of stories; rather, we should all love and respect them. Authors Ian McAllister, a founding director of both the Raincoast Conservation Society and Pacific Wild, and Nicholas Read, a journalist, pull no punches in their attempt to sway the reader. While the book does present facts about the wolves and their environment, many of them likely accurate, the authors make sweeping statements and claims which they require the reader to accept at face value. For example, though the authors state that there is “a great deal of evidence to suggest that over-fishing, fish farms and climate change have all played a role in [the wolves’] decline,” this statement does not direct the reader to any evidence. Part of the purpose of the book is to educate the reader about the wolves; however, it is also clearly designed to manipulate the readers’ emotions. The authors attempt to get the reader to identify with the wolves through anthropomorphizing the animals and by drawing extensive parallels between the lives of wolves and the lives of people. For example, they state that the reason that wolves save the “tastiest deer” for their young pups “could be because, just as in human families, wolf families like to spoil their babies.” Furthermore, throughout the book, the authors choose emotionally-laden words and images, stating, for example, that wolves “have been persecuted by humans, with a kind of madness,” or that they “romp on the beach in the ocean foam that burbles off the waves like bubble bath.” Each interpretation of the wolves’ behaviour seems designed to achieve the desired effect of garnering sympathy for the creatures. While there is nothing wrong with writing a polemic against the dangers to wolves and their environment, this book is presented by the publisher as juvenile non-fiction for ages 8 and up. Children in upper elementary or even junior high school grades may have difficulty distinguishing between facts and strongly-worded opinions presented in a book labelled as non-fiction. Recommended: Three stars out of fourReviewer: Sandy CampbellSandy is a Health Sciences Librarian at the University of Alberta, who has written hundreds of book reviews across many disciplines. Sandy thinks that sharing books with children is one of the greatest gifts anyone can give.

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 score0.044
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0440.027

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 head0.015
GPT teacher head0.352
Teacher spread0.337 · 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
Published2012
Admission routes2
Has abstractyes

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