Compliance with COVID-19 preventive measures is high among university-level students in Québec, Canada
Bibliographic record
Abstract
Background: Canada's nationwide lockdown to curb coronavirus disease 2019 (COVID-19) infections affected many sectors of activity, including universities. During the 2020-2021 academic year, all students were forced to follow their lectures from home and the only in-person activity permitted to Québec university level students was to study in designated spaces of campus libraries where COVID-19 preventive measures were in place and mandatory at all times for all staff and students. The objective of this study is to evaluate university-level students' compliance with COVID-19 preventive measures in a Québec campus library. Methods: A direct in-person evaluation by a trained observer was put in place to assess students' compliance with COVID-19 preventive measures defined as proper mask wearing and 2 meter distancing. Measurements were made each Wednesday, Saturday, and Sunday at 10 a.m., 2 p.m., and 6 p.m. from March 28 to April 25, 2021, in a university library in Québec, Canada. Results: Students' compliance with COVID-19 preventive measures was high overall (78.4%) and increased over the weeks, with differences between weeks, weekdays, and time of day. Non-compliance was lower on weeks three and four of the assessment compared with week one, and higher on Sunday compared with Wednesday. Differences seen throughout the day were not statistically significant. Non-compliance with physical distancing was rarely seen. Conclusion: Most university-level students are compliant with COVID-19 preventive measures in a Québec university library: an encouraging behaviour from a public health perspective. These findings may support public health authorities or university administrators in decisions regarding different COVID-19 preventive measures directed to different universities settings, as this method can be applied to focused, rapid observational studies and can lead to data of sufficient statistical power.
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.
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 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".