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Record W3173283536 · doi:10.29173/irie174

Wer hat unseren Kindern das Töten beigebracht? Ein Aufruf gegen Gewalt in Fernsehen, Film und Computerspielen.

2005· article· de· W3173283536 on OpenAlexvenueno aff
Thomas Hausmanninger

Bibliographic record

VenueThe International Review of Information Ethics · 2005
Typearticle
Languagede
FieldSocial Sciences
TopicPsychoanalysis and Social Critique
Canadian institutionsnot available
Fundersnot available
KeywordsGrossmanHumanitiesArt

Abstract

fetched live from OpenAlex

Review of Lt. Col. Dave Grossman and Gloria DeGaetano: Stop Teaching Our Kids to Kill. A Call to Action Against TV, Movie & Video Game Violence, New York: Crown Publications, 1999, 196 S. Lt. Col. Dave Grossman, Gloria DeGaetano: Wer hat unserem Kindern das Töten beigebracht? Ein Aufruf gegen Gewalt in Fernsehen, Film und Computerspielen. Mit Beiträgen von Prof. Werner Glogauer, Barbara Supp und Dr. Bruno Sandkühler, Stuttgart: Verlag freies Geistesleben & Urachhaus 2002, 194 S., € 14,50

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)0.006
metaresearch head score (Gemma)0.017
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: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0010.005
Scholarly communication0.0050.007
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0050.002

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 head0.046
GPT teacher head0.411
Teacher spread0.365 · 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
GenreCommentary

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

Citations1
Published2005
Admission routes1
Has abstractyes

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