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Record W7065824264

A focus on adolescent peer violence and bullying in Europe, central Asia and Canada

2024· report· en· W7065824264 on OpenAlexaboutno aff

Bibliographic record

VenueTrinity's Access to Research Output (TARA) (Trinity College Dublin) · 2024
Typereport
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsAdolescent healthSuicide preventionPoison controlIntervention (counseling)Peer groupCentral asiaHuman factors and ergonomicsOccupational safety and healthFocus group
DOInot available

Abstract

fetched live from OpenAlex

The Health Behaviour in School-aged Children (HBSC) study is a large school-based survey carried out every four years in collaboration with the
\nWHO Regional Office for Europe. HBSC data are used at national/regional and international levels to gain new insights into adolescent health
\nand well-being, understand the social determinants of health and inform policy and practice to improve young people?s lives. The 2021/2022
\nHBSC survey data are accompanied by a series of volumes that summarize the key findings around specific health topics. This report, Volume 2
\nin the series, focuses on adolescent peer violence and bullying, using the unique HBSC evidence on adolescents aged 11, 13 and 15 years across
\n44 countries and regions in Europe, central Asia and Canada. It describes the status of adolescent peer violence (bullying, cyberbullying and
\nfighting), the role of gender, age and social inequality, and how adolescent bullying and fighting behaviour has changed over time. Findings
\nfrom the 2021/2022 HBSC survey provide an important evidence benchmark for current research, intervention and policy-planning.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.094
GPT teacher head0.383
Teacher spread0.289 · 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

Citations15
Published2024
Admission routes1
Has abstractyes

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