Bibliographic record
Abstract
Navigating for accurate information, especially health- and science-related content, on social media has been challenging during the COVID-19 pandemic. Although infographics are a popular medium for simplifying text-based information into visual components, their usefulness during a global health crisis has not been explored. The study aims to explore the perceptions of infographics in conveying scientific information related to COVID-19 on social media. Following a social media campaign that published COVID-19 related infographics from May to August 2020, a cross-sectional survey was administered to social media users, primarily students from Western University. Several questions asked respondents to make comparisons with written articles when reporting their perceptions of infographics. Seventy-three percent of students from 361 responses belonged to health-related academic backgrounds. Seventy-two percent felt more likely to share infographics than written articles on social media due to the visual appeal. Nearly 90% felt it was easier to navigate through complicated science and that more scientists should use infographics on social media. Educational background did not influence the perceived usefulness of infographics in understanding scientific information. Infographics are perceived favourably in conveying scientific information about COVID-19 on social media. Findings from this study can inform communication strategies during a pandemic and, more broadly, global crises.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".