MétaCan
Menu
Back to cohort
Record W3194245755 · doi:10.1002/hbe2.282

Cybervictimization, time spent online, and developmental trajectories of online privacy concerns among early adolescents

2021· article· en· W3194245755 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHuman Behavior and Emerging Technologies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of British Columbia
FundersHealth Research
KeywordsPsychologyLongitudinal studyInternet privacyDevelopmental psychologyMedicineComputer science

Abstract

fetched live from OpenAlex

The goal of the present study was to examine developmental trajectories of online privacy concerns, as well as to identify predictive factors (e.g., cybervictimization, time spent online, and socializing online) related to online privacy concerns among early adolescents. Participants were 378 adolescents from the Lower Mainland of British Columbia, Canada who were in grade six and grade seven at wave 1 of the study (192 boys, Mage = 13.93 years, SD = .72 year). Three years of longitudinal data on online privacy concerns, cybervictimization, and time spent online socializing were collected from self-report surveys. Results identified three different trajectories of online privacy concerns: decreasing (32.8%), increasing (44.98%), and stable (22.29%). Adolescents who reported higher scores on cyber victimization were more likely to be in the decreasing online privacy. Adolescents who spent more time socializing online were more likely to be in the stable or increasing subgroup. These findings highlight the important value of studying subgroups regarding the development course of online privacy concerns.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.656

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.306
Teacher spread0.274 · 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