Inequitable Changes in School Connectedness During the Ongoing <scp>COVID</scp>‐19 Pandemic in a Cohort of Canadian Adolescents
Bibliographic record
Abstract
BACKGROUND: We examined whether subgroups of adolescents experienced disparate changes in school connectedness-a robust predictor of multiple health outcomes-from before the COVID-19 pandemic to the first full school year following pandemic onset. METHODS: We used 2 waves of prospective survey data from 7178 students attending 41 Canadian secondary schools that participated during the 2019-2020 (T1; pre-COVID-19 onset) and 2020-2021 (T2; ongoing pandemic) school years. Fixed effects analyses tested differences in school connectedness changes by gender, race, bullying victimization, socioeconomic position, and school learning mode. RESULTS: Relatively greater declines in school connectedness were reported by students that identified as females, were bullied, perceived their family to be less financially comfortable than their classmates, and attended schools in lower income areas. Marginally greater school connectedness declines resulted among students attending schools that were fully online at T2 than those at schools using a blended model. CONCLUSION: Results point to disparate school connectedness declines during the pandemic, which may exacerbate pre-existing health inequities by gender and socioeconomic position, and among bullied youth. IMPLICATIONS FOR SCHOOL HEALTH POLICY, PRACTICE, AND EQUITY: Effective strategies to improve school climates for equity denied groups are critical for pandemic recovery and preparedness for future related events.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".