Bibliographic record
Abstract
Background: Primary and secondary schools reopened after June 2020 in Canada during the pandemic while other businesses and organizations employed work-from-home policies. The reopening was to provide better options for education and well-being, but may have put educators at risk of contracting COVID-19. Aims of the CITF-funded study: The goal was to determine the prevalence of SARS-CoV-2 antibodies from infection, the psychological impact of the COVID-19 pandemic, and vaccine receptiveness among classroom educators and school staff. They also aimed to estimate asymptomatic transmission rates in schools as measured by targeted nucleic acid viral testing for SARS-CoV-2. T cell, B cell, and SARS-CoV-2 antibody assays were used to further characterize immune response to the virus. (Note: psychological impact and vaccine receptiveness data not shared with CITF Databank [1], data on asymptomatic transmission rates in children not shared with CITF Databank [2].) Methods: This cohort study recruited active school staff from the Vancouver, Delta, and Richmond school districts in British Columbia. Participants provided a blood sample for serology testing and completed online questionnaires annually at the beginning of 2021, 2022 and 2023. Contributed dataset contents: The datasets include 2444 participants who completed baseline questionnaires between February 2021 and June 2021. An additional 82 participants who did not complete a baseline questionnaire gave blood samples or follow-up surveys over the three sampling periods: approximately 87% of participants gave a blood sample between February 2021 and July 2021, 64% between January 2022 and March 2022, and 40% between January 2023 and May 2023. A total of 4828 samples were collected. Variables include data in the following areas of information: demographics (age, gender, race-ethnicity and indigeneity, education, household composition), general health (smokes; chronic conditions; height and weight; flu vaccine), COVID infection history (dates of positive PCR tests, hospitalizations, symptoms), adherence to COVID-19 public health guidelines, time spent with children, SARS-CoV-2 vaccination, and serology (antibodies against SARS-CoV-2 RBD, nucleocapsid, and spike proteins). [1]: Please contact original study team for psychological and vaccine receptiveness data. [2]: Please contact original study team for data on asymptomatic transmission rates in children.
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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.100 | 0.020 |
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".