Influence of Covid-19 Crisis Communication on Public Perception of the Kenyan Government Communication Strategy: A Case of Kibra Sub-County Nairobi, Kenya
Bibliographic record
Abstract
COVID-19 communication has drawn a sharp focus across the globe and elicited varied publicperceptions. This study sought to assess the influence of covid-19 crisis communication onpublic perception of the Kenyan government communication strategy with a case of Kibra subcounty Nairobi, Kenya, from March 2020 to December 2020. The main objective was to assesshow the government's daily speeches influenced the public interpretation of the COVID-19crisis. The rationale was based on assessing the public perception of the government’scommunication strategy. The findings of this study will be be helpful to communicationexperts and will help in improving the existing crisis communication strategies. This waslimited to Lindi ward in Kibra sub-county. Source Credibility Theory (CT) and SituationalCrisis Communication Theory (CCT) were used for understanding perception. This studyadopted a survey design to collect quantitative data involving 123 household heads sampledpurposively in Lindi, Kibra through a modified Crisis and Emergency Risk Communication(CERC) questionnaire. Averagely, 1% of the respondents disagreed with questions regardingCOVID-19 daily speeches, 8.5% indicated neutrality, and 90.5% agreed with the statements.The study concluded that the public's perceptions of government communication strategyregarding the COVID-19 crisis were favorable. The study recommends investigating theimpact of the centralization of the Kenyan government communication departments on crisiscommunication.Keywords: Crisis Communication, Public Perception, Communication Strategy
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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 | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".