Community coherence during COVID-19 – a pilot study
Bibliographic record
Abstract
Using a salutogenic perspective, this qualitative pilot study aimed to explore the experiences of university staff and students in various Western countries with community coherence during COVID-19. This entailed a focus on individual and community assets that contributed to positive experiences with community coherence during the pandemic. Sixteen participants from University staff and postgraduate students in Europe and Canada interested in Public Health were included. The study was conducted online via Microsoft Teams using the Structured Interview Matrix method. This participatory facilitating method enabled participants to dialogue about their experiences with community coherence during COVID-19. The results show that during COVID-19, participants primarily engaged in activities related to personal health and well-being, related to close family, friends and neighbours and an increased need to use digital technologies in their free time and during working hours. Key themes observed across the various international communities during the times when high levels of restrictions were in place, were a greater sense of loneliness and vulnerability. This pilot study indicates that there was a high level of community cohesion during COVID-19 and that people, despite living in different countries, were active in very similar ways.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".