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Record W2186148580

Understanding school violence: Comments on Szabo and Potterton

2009· article· en· W2186148580 on OpenAlexaboutno aff
Both Szabo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsChinaCriminologySuicide preventionWork (physics)PsychologyPolitical sciencePoison controlLawMedicineEngineeringMedical emergency
DOInot available

Abstract

fetched live from OpenAlex

1and Potterton 2 highlight the fact that violent school-related crimes occur throughout the world. School rampage shootings, such as Columbine, have in fact become commonplace in the United States and have been duplicated in Finland, Germany, Canada, China and other “peaceful” nations throughout the world. While the number of children killed in such events are few compared to those killed in car accidents, these events strike terror in the hearts of parents and children, convincing them that school is no longer a safe place. The emotional wounds and despair suffered by a community often last for decades and absorb considerable financial resources in lost work hours, school interruption and psychiatric counseling. 3 The main thrust of both editorials is to try to answer some of the questions about adolescent rampage killings. Are such incidents provoked by heavy metal music or Satanism, as the popular media would have us believe? Szabo’s points are worth repeating:

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)0.014
metaresearch head score (Gemma)0.055
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.035
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.055
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.002
Science and technology studies0.0090.016
Scholarly communication0.0090.017
Open science0.0060.005
Research integrity0.0350.063
Insufficient payload (model declined to judge)0.0030.002

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 head0.090
GPT teacher head0.331
Teacher spread0.241 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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