Public Relations in Crisis Management: A Review and Analysis of Communicative Strategies During Early Stages of Covid-19
Bibliographic record
Abstract
Since the outbreak of Covid-19 at the end of 2019, many countries face the challenges of gaining the public’s trust and encouraging collective participation in fighting against the epidemic and national crisis. Different countries applied different communication strategies to cope with the critical situation. Many of these approaches have been criticized for their effectiveness. Therefore, this review article critically examines it through the lens of crisis management and communicative strategies, particularly its application in the early stages of Covid-19. It explores crisis communication from three angles: content, channels, and key difficulties during the early stages of the pandemic. Highlighting fear's dual role in crisis management and the challenges of misinformation on social media, it emphasizes the need for dynamic fear negotiation and enhanced health literacy. The review offers insights for future studies on fear communication and misinformation, stressing the importance of improving online representation of medical professionals to establish trust and regulate public behavior during 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".