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Record W4246680346 · doi:10.1353/bcc.2006.0834

Skinnybones and the Wrinkle Queen (review)

2006· article· en· W4246680346 on OpenAlexaboutno aff
Karen Coats

Bibliographic record

VenueBulletin of the Center for Children's Books./Bulletin of the Center for Children's Books · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsnot available
Fundersnot available
KeywordsQueen (butterfly)Art historyLawSociologyArtPolitical science

Abstract

fetched live from OpenAlex

Reviewed by: Skinnybones and the Wrinkle Queen Karen Coats Huser, Glen Skinnybones and the Wrinkle Queen. Groundwood/House of Anansi, 2006232p ISBN 0-88899-732-9$16.95 R Gr. 7-10 Disaffected Tamara has been bounced into yet another foster home, but this time she is really going to try to follow her case worker's advice and be more positive. She still skips school to get her real education, though, spending as much time as she can watching fashion programs to prep for a modeling career. When a school service assignment teams her up with Miss Barclay, a cigarillo-smoking, brandy-sneaking elderly woman in a nursing home, they soon figure out that they can use each other to get what they want—Miss Barclay will pay for a weeklong modeling workshop in Vancouver if Tamara will drive her to Seattle for Wagner's Ring Cycle. Knowing that their respective caretakers will never approve, the two pull a Thelma and Louise and almost get away with it. Like Fleischman's Mind's Eye (BCCB 10/99), the novel sets up a likely/unlikely pair, both painfully aware of what they want and the limitations that keep them from it. Unlike Fleischman's pair, however, Miss Barclay and Tamara are equally matched for short tempers and grumpiness, and Miss Barclay turns out to be more unruly than Tamara. Chapters alternate first-person perspectives so readers get a chance to hear all that goes unsaid between the two and to see the generational and economic gaps in taste and values without any outside or heavy-handed arbitration. Both characters emerge as strongly [End Page 173] sympathetic rebels; readers will applaud their outlaw partnership and be glad that Tamara, at least, receives forgiveness and a fresh start. Copyright © 2006 The Board of Trustees of the University of Illinois

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.599
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.000
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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2006
Admission routes1
Has abstractyes

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