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Record W2559310985 · doi:10.1177/2056305116680005

“Honestly, We’re Not Spying on Kids”: School Surveillance of Young People’s Social Media

2016· article· en· W2559310985 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

VenueSocial Media + Society · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEspionageSocial mediaSocializationRaising (metalworking)Internet privacyActive listeningPublic relationsPolitical scienceData collectionSociologyEngineeringLawComputer scienceSocial science

Abstract

fetched live from OpenAlex

Social media is one of the top activities and sites for young people’s socialization in North America, raising concerns over their social privacy, because of reported instances of cyberbullying and sexting, and their informational privacy, because of commercial data collection. A trend in schools and school districts in the United States is to monitor and track, through third party applications and software, student social media during and after school, in an attempt to prevent or reduce the perceived dissemination of violence, bullying, threats, or hate instigated by students and directed toward other students or entire schools. This article will provide an overview of four of these US companies (Geo Listening, Varsity Monitor, Snaptrends, Digital Fly) and consider the policy and ethical issues of data monitoring with respect to young people’s rights to privacy and their freedom of speech.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.040
GPT teacher head0.301
Teacher spread0.261 · 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