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Record W4230630424 · doi:10.1017/cbo9781139095891

Sexting and Cyberbullying

2014· book· en· W4230630424 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCambridge University Press eBooks · 2014
Typebook
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsMcGill University
Fundersnot available
KeywordsPolitical scienceValue (mathematics)CriminologyPublic relationsHuman rightsSociologyPsychologyLaw

Abstract

fetched live from OpenAlex

Directed at policy makers, legislators, educators, parents, the legal community, and anyone concerned about current public policy responses to sexting and cyberbullying, this book examines the lines between online joking and legal consequences. It offers an analysis of reactive versus preventive legal and educational responses to these issues using evidence-based research with digitally empowered kids. Shaheen Shariff highlights the influence of popular and 'rape' culture on the behavior of adolescents who establish sexual identities and social relationships through sexting. She argues that we need to move away from criminalizing children and toward engaging them in the policy development process, and she observes that important lessons can be learned from constitutional and human rights frameworks. She also draws attention to the value of children's literature in helping the legal community better understand children's moral development and in helping children clarify the lines between harmless jokes and harmful postings that could land them in jail.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.178
Teacher spread0.167 · 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