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Record W2602149964

"The Child's Education to Violence" Mrs. Eleanor Gray and the Canadian Crusade to Ban Crime Comics

2016· article· en· W2602149964 on OpenAlexaffabout
Alastair Glegg

Bibliographic record

VenueThe Journal of Teaching and Learning · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComicsGray (unit)ParliamentCriminologyMedia studiesLawPolitical scienceThe InternetOrganised crimeSociologyPolitics
DOInot available

Abstract

fetched live from OpenAlex

Contemporary concerns over the prevalence of violence on the internet and in films and the impact on young people are not without precedent. In the 1940s and 1950s there was a campaign to eliminate the so-called crime comics, led in Canada by Mrs. Eleanor Gray of Victoria, British Columbia. Based primarily on her own correspondence and documents which she donated to the Provincial Archives of British Columbia in 1978, this paper traces her part in the campaign, which eventually succeeded in persuading parliament to change the Criminal Code of Canada. It also compares the campaign with other social reform movements of the period, and notes the change in public attitude which now views the same comics not as a menace to society but as innovative and important art forms.

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)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0290.017
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0090.001

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 head0.228
Teacher spread0.219 · 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
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
Published2016
Admission routes2
Has abstractyes

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