A Prospective and Repeat Cross-Sectional Study of Bullying Victimization Among Adolescents From Before COVID-19 to the Two School Years Following the Pandemic Onset
Bibliographic record
Abstract
We examined bullying victimization spanning from before the pandemic to the two school years post COVID-19 onset in adolescents. We used survey data from Canadian secondary school students collected during the 2019–20, 2020–21, and 2021–22 academic years. Generalized Estimating Equations models were used to estimate the population average odds of past 30-day bullying victimization by other students, using both longitudinal (N = 3716) and repeat cross-sectional (N = 23,862; 19,413; 21,897) data. The odds of bullying victimization were lower in 2020–21 and higher in 2021–22 relative to 2019–20. Elevated odds of bullying victimization were found among gender diverse, higher weight, and relatively less affluent students. While remote schooling during the pandemic may have provided a reprieve for some students, bullying appears to have rebounded with the lifting of COVID-19 restrictions to exceed pre-pandemic levels. More effective strategies are essential to prevent bullying and improve school contexts for equity denied populations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".