Cybervictimization, time spent online, and developmental trajectories of online privacy concerns among early adolescents
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".