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Record W2296498235 · doi:10.20361/g2q306

Seeing Red: The True Story of Blood by T. L. Kyi

2012· article· en· W2296498235 on OpenAlexvenueaboutno aff
Elizabeth Wallace

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsComicsAdventureNarrativeLiteratureArt historyArtSubject (documents)HistoryLibrary scienceComputer science

Abstract

fetched live from OpenAlex

Kyi, Tanya L. Seeing Red: The True Story of Blood. Illus. Steve Rolston. Toronto: Annick Press, 2012. Print. Seeing Red is an informative, humourous, gory, and decidedly irreverent treatment of a subject close to all of our hearts. Canadian author Tanya Lloyd Kyi is best known for the 50 Questions series for young readers, featuring topics as diverse as fire, poison and underwear. The very clever illustrations, by award-winning comic and graphic novel artist Steve Rolston, are presented in shades of black, grey, and (naturally) blood red. The main narrative provides a fascinating overview of the red stuff, human and otherwise, and the central role it has played in history, culture, and science. Alongside the text in each chapter, the reader is treated to a comic book featuring (in a nod to Bram Stoker) a boy named Harker who keeps a notebook of his blood-filled adventures as he finds himself at the centre of the topic under discussion. And throughout, the author provides a wealth of related trivia and factoids using insets on subtle background graphics of red blood cells and band aids. Individual chapters focus on ritual and religion, coming of age, food and drink, family ties and genetics, medicine and forensics, and the human fascination with violence. And while not following a strict chronology, the author clearly demonstrates how human understanding of this vital fluid has developed throughout history. The chapter Rites of Passage should be of particular interest to pre-teens, with its graphic descriptions of how various cultures have developed painful and bloody initiation rituals to mark a boy’s transition to adulthood, and of the wide range of celebrations and taboos surrounding a girl’s first menstrual period. The ever-popular vampire is featured no more prominently than any other topic in the text, with only a couple of sections in the chapter Sips and Suppers that discusses the utility of blood in all manner of drinking and dining. But the introduction of a cute young female vampire to Harker’s story midway through the book will no doubt appease any disappointed Twilight fans. Pop culture references abound, and the author’s black humour skewers major religions and historical figures alike. A discussion of hemophilia features an illustration of Queen Victoria handing a jumbo pack of bandages to her daughter with the words “Don’t forget your dowry dear.” There’s no lack of gory detail in this book, from Aztec priests ripping beating hearts from the chests of their captives, to classifications of blood spatter velocities and how they correspond to different levels of violent injury. This book would be a great addition to any public or school library. Each chapter ends with a few questions from Harker’s notebook that may provide some interesting starting points for classroom discussion: “Is it okay to sacrifice animals for religious reasons? How is that different than killing for meat, or hunting for sport?” The reader is provided with a list of titles for further reading, and a selected bibliography. And with its fairly in-depth indexing, Seeing Red provides a handy reference to a lot of bloody information. Highly recommended: 4 out of 4 stars Reviewer: Elizabeth WallaceElizabeth Wallace is the Collections Manager in the Science and Technology Library of the University of Alberta. She holds an undergraduate degree in Geography and Environmental Studies, and an MLIS, both from McGill University. She has been a Science and Engineering librarian for her entire professional career, working in both public and academic libraries in the U.S. and Canada.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.896
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.269
Teacher spread0.263 · 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.

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
Published2012
Admission routes2
Has abstractyes

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