The Covid-19 pandemic in Ghana: exploring the discourse strategies in president Nana Addo’s speeches
Bibliographic record
Abstract
Abstract Communication during a crisis can affect crisis management and health outcomes. Only a few studies in Africa have examined political leaders’ speeches on Covid-19 pandemic preventive and restrictive lockdown measures. The purpose of this study is to examine the discourse strategies employed in President Nana Addo’s speeches delivered to Ghanaians on the measures taken to combat the coronavirus. The first ten speeches of Nana Addo since the inception of Covid-19 were selected, coded, and examined using content thematic analysis. The analysis of these speeches identified five main themes to capture the discourse strategies which President Nana Addo used. The strategies captured in the thematic analysis included framing Covid-19 as a war, encouraging nationalism and patriotism, showing appreciation and gratitude, threatening sanctions, and using religious values. These strategies were reinforced by using religious, moralizing, and national identity legitimation discourses to justify measures the government had put in place to minimize the impact of Covid-19 and improve healthcare response. Also, the historical, social, and political contexts of Ghana and elsewhere were invoked in Nana Addo’s speeches to legitimize the government’s response to Covid-19. In conclusion, we highlight the implications of these strategies on crisis communication and management.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".