Alfabetización estadística y comunicación de riesgo para la vacunación contra la COVID-19: una revisión de alcance
Bibliographic record
Abstract
OBJECTIVE: To describe the role of statistical literacy and proper risk communication in communication strategies related to COVID-19 vaccination. METHODS: A scoping review was carried out in January 2021, with the keywords "statistical literacy," "risk communication," "health communication," and "pandemic," in the Pan American Health Organization Virtual Health Library, PubMed, Web of Science, EBSCO, and Google Scholar databases. No filters were applied for dates, language, or publication type. RESULTS: Of the 87 articles identified, four met the inclusion criteria. Four main messages were recognized that relate statistical literacy and risk communication: 1) risk communication and statistical literacy level affect individual and collective decision-making; 2) communication of uncertainty should include what is known and not known with regard to statistics and risks; 3) the use of graphics and visuals is key to appropriately informing the population; and 4) different formats should be used to improve communication, always adjusted to the population's statistical literacy level. CONCLUSIONS: Statistical literacy plays a key role in communicating risks related to health in general and COVID-19 vaccination in particular. In health emergencies, proper communication of risk and associated uncertainty should be clear, transparent, and timely.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".