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Record W4231690464 · doi:10.1353/bcc.2006.0559

My Dad's a Punk (review)

2006· article· en· W4231690464 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
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsPunkWhite (mutation)Art historyHistoryMedia studiesSociologyArt

Abstract

fetched live from OpenAlex

Reviewed by: My Dad's a Punk Karen Coats Bradman, Tony , ed. My Dad's a Punk. Kingfisher, 2006271 p Paper ed. ISBN0-7534-5870-5$7.95 R Gr. 5-8 With writers from Britain, Canada, Australia, and the U.S. (including notables such as Ron Koertge and Tim Wynne-Jones), these twelve stories about boys and their fathers take readers to places far away from wherever they sit, from tiny cabins in remote Canadian towns, to "halfway between Nowhere and Nowhere Else, Arizona," to a suburban landscape of the future, to the inside of a tank during World War II. There they encounter fathers—a failed magician, a straitlaced soldier, a blockade-running sailor, a salesman who is too busy for his son, and a doctor and punk rocker whose sons wish their fathers were too busy for them. Many of the fathers are divorced from the mothers, most are white, some are dead, some gay, some angry, some heroic, some embarrassing, but all forge loving, ultimately supportive relationships with their sons. Indeed, despite the provocative-sounding title, the stories contained here are by turns funny, grim, and warm-hearted but never angry, edgy, or wrenching; the punk dad is in fact a guy who has spiky hair and a fondness for the Pogues and who plays in a band called "Bucket of Snot." "You get used to it," says the narrator of his story, and indeed that seems to be the reigning wisdom of all of these stories: dads, no matter what their weirdnesses and hang-ups are, are people you get used to, people who are good to have around, even if you have to work hard to understand and even protect them from your own critical judgments. Readers looking for something harsher or with more grit will have to look elsewhere, but these are solid stories with high-interest plots and mostly feel-good resolutions, just right for the audience. 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 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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.929
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0710.023

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 head0.009
GPT teacher head0.188
Teacher spread0.178 · 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.

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
Published2006
Admission routes1
Has abstractyes

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